Information generation method and system based on microwave network test of super large open-pit mine

Abstract

The application provides a method and system for generating information based on microwave network testing of a super-large open-pit mine, and relates to the field of artificial intelligence. The method comprises the following steps: for a target microwave network layout task corresponding to a target open-pit mine, determining target microwave network description data corresponding to the target microwave network layout task and microwave network related data corresponding to the target microwave network layout task; correlatively mining microwave network testing target information, microwave network current information and the microwave network related data to form a microwave network layout vector corresponding to the target microwave network layout task; loading the microwave network layout vector into an updated microwave layout analysis network, and using the microwave layout analysis network to analyze and generate at least one piece of microwave network layout target information matched with the microwave network testing target information. Based on the above, the reliability of microwave network layout generation can be improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of artificial intelligence, in particular to a microwave network test information generation method and system based on super large open-pit mine. BACKGROUND

[0002] Super large open-pit mine refers to a large-scale open-pit mining site used for mining various mineral resources. Such mines are usually located on the surface rather than underground. Super large open-pit mines generally have a wide area and depth, and mining is carried out through large mechanical equipment and blasting techniques. These mines can be found worldwide, including iron ore, coal, copper ore, gold, diamonds, etc. Therefore, in super large open-pit mines, there are many devices involved, so in order to ensure reliable communication of each device in the super large open-pit mine, there is a certain requirement for the network quality of the microwave communication network deployed therein. For example, when it is tested that the current network quality does not meet the requirements, the layout of the microwave communication network needs to be improved so that the network quality meets the requirements. Therefore, it is necessary to generate a corresponding microwave communication network layout for the target network quality, but in the prior art, the layout of the microwave network is generally generated manually based on the target network quality. Due to the existence of misoperation or analysis errors in the manual operation process, the reliability of the method in the prior art is relatively low. SUMMARY

[0003] The main purpose of the present application is to provide a microwave network test information generation method and system based on super large open-pit mine, to at least solve the problem of low reliability of the microwave layout network generation method in the prior art.

[0004] In order to achieve the above object, according to one aspect of the present application, a method for generating information based on microwave network testing of super large open-pit mine is provided, comprising: determining target microwave network description data corresponding to a target microwave network layout task of a target open-pit mine and microwave network related data corresponding to the target microwave network layout task, the target microwave network description data including microwave network current information and microwave network testing target information, the microwave network current information including microwave network testing current information and microwave network layout current information, the microwave network testing current information being used to reflect signal testing quality of a current microwave network corresponding to the microwave network layout current information, the microwave network testing target information being used to reflect signal testing quality of an improved microwave network; correlatively mining the microwave network testing target information, the microwave network current information and the microwave network related data to form a microwave network layout vector corresponding to the target microwave network layout task, the microwave network layout vector being used to reflect semantic features of the microwave network testing target information, the microwave network current information and the microwave network related data; loading the microwave network layout vector into an updated microwave layout analysis network, and using the microwave layout analysis network to analyze and generate at least one microwave network layout target information matching the microwave network testing target information, the microwave network layout target information being used to reflect layout information of the improved microwave network.

[0005] Optionally, the correlatively mining the microwave network testing target information, the microwave network current information and the microwave network related data to form the microwave network layout vector corresponding to the target microwave network layout task comprises: combining the microwave network testing current information and the microwave network layout current information in the microwave network current information and the microwave network testing target information to form to-be-processed sequence data; mining a first microwave network layout vector corresponding to the target microwave network layout task according to the to-be-processed sequence data; mining a second microwave network layout vector corresponding to the target microwave network layout task according to the microwave network related data; and aggregating the first microwave network layout vector and the second microwave network layout vector to form the microwave network layout vector corresponding to the target microwave network layout task.

[0006] Optionally, the microwave network related data further comprises microwave network environment data and team description data of an improvement team of the target microwave network layout task, the improvement team comprising improvement personnel and improvement equipment, and the second microwave network layout vector corresponding to the target microwave network layout task is mined according to the microwave network related data, comprising: mining a microwave network related vector of the microwave network environment data and a microwave network related vector of the team description data; and aggregating the microwave network related vectors of the microwave network environment data and the team description data included in the microwave network related data to form the second microwave network layout vector corresponding to the target microwave network layout task.

[0007] Optionally, the first microwave network layout vector corresponding to the target microwave network layout task is mined according to the to-be-processed sequence data, comprising: obtaining data unit features of each data unit included in the to-be-processed sequence data, and combining the data unit features of the data units according to the sequence of the data units in the to-be-processed sequence data to form a corresponding first local network layout vector; obtaining, for each data unit in the to-be-processed sequence data, segment flag data of a sequence segment to which the data unit belongs, the granularity of the data unit being a word, a phrase or a sentence, and the sequence segment being microwave network test current information, microwave network layout current information or the microwave network test target information in the microwave network current information; combining the segment flag data corresponding to the data units according to the sequence of the data units in the to-be-processed sequence data to form a second local network layout vector; obtaining coordinate flag data of the data units in the to-be-processed sequence data; combining the coordinate flag data corresponding to the data units according to the sequence of the data units in the to-be-processed sequence data to form a third local network layout vector; and aggregating the first local network layout vector, the second local network layout vector and the third local network layout vector to form the first microwave network layout vector corresponding to the target microwave network layout task.

[0008] Optionally, the microwave network layout vector is loaded into the updated microwave layout analysis network, and at least one piece of microwave network layout target information matched with the microwave network test target information is analyzed by using the microwave layout analysis network, including: loading the microwave network layout vector into the microwave layout analysis network, and analyzing at least one first undetermined data unit corresponding to the microwave network test target information, the granularity of the undetermined data unit being a word, a phrase, or a sentence; combining each first undetermined data unit at the tail of the microwave network test target information, and taking each combined extended data as an extended microwave network test target information to form at least one extended microwave network test target information, in the process of forming the microwave network layout vector corresponding to the target microwave network layout task in the formed to-be-processed sequence data, the microwave network test target information is arranged at the last; for each extended microwave network test target information, an extended microwave network layout vector corresponding to each extended microwave network test target information is determined according to the microwave network current information and the microwave network related data; each extended microwave network layout vector is loaded into the microwave layout analysis network to analyze at least one second undetermined data unit; when the second undetermined data unit belongs to an end flag data, the first undetermined data unit and the second undetermined data unit are combined to form at least one piece of microwave network layout target information matched with the microwave network test target information.

[0009] Optionally, loading the microwave network layout vector into the microwave layout analysis network to analyze at least one first undetermined data unit corresponding to the microwave network test target information includes: loading the microwave network layout vector into the microwave layout analysis network to analyze a plurality of microwave layout analysis data corresponding to the microwave network test target information, each microwave layout analysis data including an original data unit and a prediction probability of the original data unit; according to the size relationship of the corresponding prediction probability, a plurality of original data units are sorted to form a corresponding original data unit sequence; in the original data unit sequence, each original data unit is iterated in turn according to the order of the corresponding prediction probability from large to small, and the prediction probability corresponding to each original data unit that is currently iterated is accumulated; after each accumulation, the size relationship between the current obtained accumulation result and a preset parameter is judged, and in the case that the current obtained accumulation result is less than the preset parameter, the next original data unit is iterated, or in the case that the current obtained accumulation result is greater than or equal to the preset parameter, each original data unit that is currently iterated is taken as at least one first undetermined data unit corresponding to the microwave network test target information.

[0010] Optionally, for each of the extended microwave network test target information, according to the microwave network current information and the microwave network related data, an extended microwave network layout vector corresponding to each of the extended microwave network test target information is determined, including: combining the microwave network test current information and the microwave network layout current information in the microwave network current information, and the extended microwave network test target information, to form an extended to-be-processed sequence data; according to the extended to-be-processed sequence data, an extended first microwave network layout vector corresponding to the target microwave network layout task is mined; according to the microwave network related data, a second microwave network layout vector corresponding to the target microwave network layout task is mined; and the extended first microwave network layout vector and the second microwave network layout vector are aggregated to form the extended microwave network layout vector corresponding to the target microwave network layout task.

[0011] Optionally, the network updating process of the microwave layout analysis network includes: determining an example information cluster, the example information cluster including a plurality of example information, each example information including example microwave network description data, example microwave network layout target information and example microwave network related data corresponding to an example microwave network layout task, the example microwave network layout target information being the layout information of an improved example microwave network corresponding to the example microwave network description data; for each example information, according to the example microwave network description data and the example microwave network related data included in the example information, an example microwave network layout vector corresponding to the example microwave network description data is associatedly mined; and according to the example microwave network layout vector and the example microwave network layout target information corresponding to each of the example information, a candidate microwave layout analysis network is updated as follows: for each of the example information, the example microwave network layout vector corresponding to the example information is loaded into the candidate microwave layout analysis network, and the candidate microwave layout analysis network is used to analyze and generate at least one estimated microwave network layout target information corresponding to the example microwave network layout vector; according to the at least one estimated microwave network layout target information and the example microwave network layout target information corresponding to each of the example information, a network updating error corresponding to the candidate microwave layout analysis network is calculated; when the network updating error is less than a preset error, the current candidate microwave layout analysis network is taken as an updated microwave layout analysis network; when the network updating error is greater than or equal to the preset error, the network parameters of the candidate microwave layout analysis network are updated according to the network updating error, and the current updated candidate microwave layout analysis network is continuously updated according to the example microwave network layout vector and the example microwave network layout target information corresponding to each of the example information.

[0012] Optionally, after loading the microwave network layout vector into the updated microwave layout analysis network, using the microwave layout analysis network to analyze at least one piece of microwave network layout target information matched with the microwave network test target information, the method further comprises: when the number of the microwave network layout target information matched with the microwave network test target information is equal to 1, taking the microwave network layout target information as the final output data of the target microwave network layout task; when the number of the microwave network layout target information matched with the microwave network test target information is greater than 1, respectively calculating the similarity between each microwave network layout target information and the current microwave network layout information, and taking the microwave network layout target information with the maximum similarity as the final output data of the target microwave network layout task.

[0013] According to another aspect of the present application, there is provided an information generation system based on microwave network testing of super large open-pit mine, characterized in that it comprises one or more processors, a memory, and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the one or more processors, and the one or more programs comprise programs for executing any one of the methods.

[0014] With the technical scheme of the present application, in the information generation method based on microwave network testing of super large open-pit mine, first, for the target microwave network layout task corresponding to the target open-pit mine, the target microwave network description data corresponding to the target microwave network layout task and the microwave network related data corresponding to the target microwave network layout task are determined, the target microwave network description data includes microwave network current information and microwave network testing target information, the microwave network current information includes microwave network testing current information and microwave network layout current information, the microwave network testing current information is used to reflect the signal testing quality of the current microwave network corresponding to the microwave network layout current information, and the microwave network testing target information is used to reflect the signal testing quality of the improved microwave network; then, the microwave network testing target information, the microwave network current information and the microwave network related data are associated and mined to form a microwave network layout vector corresponding to the target microwave network layout task, the microwave network layout vector is used to reflect the semantic features of the microwave network testing target information, the microwave network current information and the microwave network related data; finally, the microwave network layout vector is loaded into the microwave layout analysis network subjected to updating processing, and at least one piece of microwave network layout target information matched with the microwave network testing target information is generated by using the microwave layout analysis network, the microwave network layout target information is used to reflect the layout information of the improved microwave network. In the scheme of the present application, when generating the microwave network layout target information, not only the microwave network testing target information, but also the microwave network testing current information and the microwave network layout current information are used, so that the microwave network layout target information is more matched with the microwave network testing current information and the microwave network layout current information, and the current microwave network is facilitated to be improved. Therefore, the reliability of the microwave network layout generation is improved, thereby improving the problem of relatively low reliability in the prior art. In addition, the microwave network related data is also used, so that the basis for analysis is more sufficient, thereby improving the reliability. BRIEF DESCRIPTION OF DRAWINGS

[0015] Figure 1 A hardware structure block diagram of a mobile terminal according to the information generation method based on microwave network testing of super large open-pit mine provided in an embodiment of the present application is shown;

[0016] Figure 2 A flowchart of the information generation method based on microwave network testing of super large open-pit mine provided in an embodiment of the present application is shown;

[0017] Figure 3 A structure block diagram of an information generation device based on microwave network testing of super large open-pit mine provided in an embodiment of the present application is shown;

[0018] Figure 4 A structural block diagram of an information generation system based on a microwave network test of a super-large open-pit mine according to an embodiment of the present application is shown.

[0019] In the above drawings, the following reference signs are used:

[0020] 102, processor; 104, memory; 106, transmission device; 108, input / output device. DETAILED DESCRIPTION

[0021] It should be noted that the embodiments and features in the present application can be combined with each other without conflict. The present application will be described in detail below with reference to the drawings and in combination with the embodiments.

[0022] In order for those skilled in the technical field to better understand the present application, the technical solutions in the embodiments of the present application will be described clearly and completely below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, not all. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor should be within the scope of protection of the present application.

[0023] It should be noted that the terms "first", "second", etc. in the specification and claims of the present application and the above drawings are used to distinguish similar objects, and do not necessarily describe a specific order or sequence. It should be understood that the data used in this way can be interchanged under appropriate circumstances, so that the embodiments of the present application described herein. In addition, the terms "include" and "have" and any variations thereof are intended to cover non-exclusive inclusion, for example, a process, method, system, product or device that includes a series of steps or units does not necessarily limit to those steps or units clearly listed, but can include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0024] As introduced in the background, the information generation method of the prior art in the microwave network test relies on manual operation, and the reliability is low. To solve the problem of low reliability of the microwave layout network generation method in the prior art, the embodiments of the present application provide an information generation method and system based on a microwave network test of a super-large open-pit mine.

[0025] The technical solutions in the embodiments of the present application will be described clearly and completely below with reference to the drawings in the embodiments of the present application.

[0026] The method embodiments provided in the embodiments of the present application can be executed in a mobile terminal, a computer terminal or a similar computing device. Taking the case of running on a mobile terminal, Figure 1This is a hardware structure block diagram of a mobile terminal of an information generation method based on a large open-pit mine microwave network test according to an embodiment of the present invention. Figure 1 As shown, the mobile terminal may include one or more ( Figure 1 Only one is shown) a processor 102 (the processor 102 may include but is not limited to a microprocessor MCU or a programmable logic device FPGA and other processing devices) and a memory 104 for storing data, wherein the mobile terminal may also include a transmission device 106 and an input and output device 108 for communication functions. It will be understood by those skilled in the art that Figure 1 The structure shown is only for illustration and does not limit the structure of the mobile terminal. Figure 1 More or fewer components than shown, or with Figure 1 Different configurations shown.

[0027] The memory 104 can be used to store computer programs, such as software programs and modules of application software, such as the computer program corresponding to the device information display method in the embodiment of the present invention. The processor 102 executes various functional applications and data processing by running the computer program stored in the memory 104, that is, implementing the above-mentioned method. The memory 104 may include a high-speed random access memory and may also include a non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some examples, the memory 104 may further include a memory remotely located relative to the processor 102, and these remote memories can be connected to the mobile terminal via a network. Examples of the above-mentioned networks include but are not limited to the Internet, corporate intranets, local area networks, mobile communication networks, and combinations thereof. The transmission device 106 is used to receive or send data via a network. Specific examples of the above-mentioned network may include a wireless network provided by the mobile terminal's communication provider. In one example, the transmission device 106 includes a network adapter (Network Interface Controller, abbreviated as NIC), which can be connected to other network devices via a base station to communicate with the Internet. In one example, the transmission device 106 may be a radio frequency (RF) module, which is used to communicate with the Internet wirelessly.

[0028] In this embodiment, a method for generating information based on a microwave network test of an extra-large open-pit mine is provided, which runs on a mobile terminal, a computer terminal or a similar computing device. It should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a set of computer executable instructions, and although a logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in an order different from that shown here.

[0029] Figure 2 is a flowchart of an information generation method based on microwave network testing of a super-large open-pit mine according to an embodiment of the present application. As shown in the figure, the method comprises the following steps: Figure 2

[0030] In step S201, the microwave network related data corresponding to the target microwave network layout task is determined, the target microwave network description data corresponding to the target microwave network layout task is determined, the target microwave network description data comprises microwave network current information and microwave network testing target information, the microwave network current information comprises microwave network testing current information and microwave network layout current information, the microwave network testing current information is used to reflect the signal testing quality of the current microwave network corresponding to the microwave network layout current information, and the microwave network testing target information is used to reflect the signal testing quality of the improved microwave network.

[0031] Specifically, for the target microwave network layout task corresponding to the target open-pit mine, the target microwave network description data corresponding to the target microwave network layout task and the microwave network related data corresponding to the target microwave network layout task are determined, that is, the information generation system based on microwave network testing of a super-large open-pit mine determines the target microwave network description data corresponding to the target microwave network layout task and the microwave network related data (such as microwave network environment data, including weather conditions (such as rain, snow, heavy fog) and terrain information) corresponding to the target microwave network layout task for the target microwave network layout task corresponding to the target open-pit mine. The target microwave network description data comprises microwave network current information and microwave network testing target information, the microwave network current information comprises microwave network testing current information and microwave network layout current information, the microwave network testing current information is used to reflect the signal testing quality (signal strength, signal-to-noise ratio, bit error rate, etc.) of the current microwave network corresponding to the microwave network layout current information (such as the current position and number of microwave communication equipment (such as antennas and repeaters) in the mine site), and the microwave network testing target information is used to reflect the signal testing quality of the improved microwave network.

[0032] In step S202, the microwave network testing target information, the microwave network current information and the microwave network related data are associated and mined to form a microwave network layout vector corresponding to the target microwave network layout task, and the microwave network layout vector is used to reflect the semantic features of the microwave network testing target information, the microwave network current information and the microwave network related data.

[0033] ​Specifically, the above-mentioned microwave network test information generation system based on super large open-pit mine can associate and mine the above-mentioned microwave network test target information, the above-mentioned microwave network current information and the above-mentioned microwave network related data to form a microwave network layout vector corresponding to the above-mentioned microwave network test target information. The above-mentioned microwave network layout vector is used to reflect the semantic characteristics possessed by the above-mentioned microwave network test target information, the above-mentioned microwave network current information and the above-mentioned microwave network related data. That is, the above-mentioned microwave network layout vector not only carries the information of the required signal quality, but also carries the information of the current layout, and the related information of the microwave network.

[0034] In step S203, the above-mentioned microwave network layout vector is loaded into the updated microwave layout analysis network, and the above-mentioned microwave layout analysis network is used to analyze and generate at least one microwave network layout target information matched with the above-mentioned microwave network test target information. The above-mentioned microwave network layout target information is used to reflect the layout information of the improved microwave network.

[0035] Specifically, the above-mentioned microwave network test information generation system based on super large open-pit mine can associate and mine the above-mentioned microwave network test target information, the above-mentioned microwave network current information and the above-mentioned microwave network related data to form a microwave network layout vector corresponding to the above-mentioned microwave network test target information. The above-mentioned microwave network layout vector is used to reflect the semantic characteristics possessed by the above-mentioned microwave network test target information, the above-mentioned microwave network current information and the above-mentioned microwave network related data. That is, the above-mentioned microwave network layout vector not only carries the information of the required signal quality, but also carries the information of the current layout, and the related information of the microwave network.

[0036] In a specific implementation, a microwave network includes: microwave antennas: devices for transmitting and receiving microwave signals, which can be directional antennas or sector antennas; relay stations: relay stations are used to amplify and forward microwave signals to extend the communication distance; transmission equipment: these devices are responsible for transmitting signals from one place to another, which can include microwave link equipment, transmission stations (adapters), etc.; modems: used to convert digital signals into analog signals (modulation) and restore digital signals from analog signals (demodulation), which are used for encoding and decoding data in microwave communication systems; wireless switches: used to manage and control data transmission of microwave communication networks, which can handle data routing, frequency selection, signal scheduling, etc.

[0037] In a specific scenario of one embodiment, the device distribution of the microwave communication network in a large-scale open-pit mine (i.e., the current information of the microwave network layout) is as follows:

[0038] Microwave antennas: 10 microwave antennas are installed in area A, each with a coverage radius of 3 kilometers; 8 microwave antennas are installed in area B, each with a coverage radius of 2.5 kilometers; 12 microwave antennas are installed in area C, each with a coverage radius of 4 kilometers;

[0039] Relay stations: Relay station A is located between area A and area B; Relay station B is located between area B and area C; Relay station C is located between area A and area C;

[0040] Transmission equipment: from relay station A to relay station B, a set of microwave link equipment is used for signal transmission; from relay station B to relay station C, a set of microwave link equipment is used for signal transmission; from relay station A to relay station C, a set of microwave link equipment is used for signal transmission;

[0041] Modem: each microwave antenna, relay station, and transmission equipment is equipped with a modem to realize the encoding and decoding functions of the signal;

[0042] Wireless switch: a wireless switch is set up between relay station A, relay station B, and relay station C, respectively, to manage and control data transmission.

[0043] Further, the current information of the above microwave network test is as follows:

[0044] Signal strength test: test type: signal strength; test parameters: frequency range: 2-6 GHz; measurement point location: 10 key locations are selected, including microwave antennas, relay stations, and device access points; test duration: 5 minutes per location;

[0045] Signal-to-noise ratio test: test type: signal-to-noise ratio; test parameters: frequency range: 2-6 GHz; measurement point location: 8 representative locations are selected, covering different areas and distances from the relay station; test duration: 10 minutes per location;

[0046] Bit error rate test: test type: bit error rate; test parameters: frequency range: 2-6 GHz; measurement point location: 5 key locations are selected, including locations far from the relay station or locations with large signal attenuation; test duration: 30 minutes per location;

[0047] Among the 10 test points, the signal strength of each test point is as follows: test point 1: -50dBm; test point 2: -45dBm; test point 3: -48dBm; test point 4: -52dBm; test point 5: -55dBm; test point 6: -48dBm; test point 7: -46dBm; test point 8: -51dBm; test point 9: -53dBm; test point 10: -47dBm;

[0048] Among the 8 test points, the signal-to-noise ratio of each test point is as follows: test point 1: 25dB; test point 2: 23dB; test point 3: 26dB; test point 4: 21dB; test point 5: 20dB; test point 6: 22dB; test point 7: 24dB; test point 8: 27dB;

[0049] Among the 5 test points, the bit error rate of each test point is as follows: test point 1: 0.05%; test point 2: 0.03%; test point 3: 0.06%; test point 4: 0.02%; test point 5: 0.04%.

[0050] Suppose the above microwave network test target information is:

[0051] Among the 10 test points, the signal strength of each test point is as follows: test point 1: -48dBm; test point 2: -43dBm; test point 3: -46dBm; test point 4: -50dBm; test point 5: -52dBm; test point 6: -47dBm; test point 7: -45dBm; test point 8: -49dBm; test point 9: -51dBm; test point 10: -46dBm;

[0052] Among the 8 test points, the signal-to-noise ratio of each test point is as follows: test point 1: 28dB; test point 2: 26dB; test point 3: 29dB; test point 4: 24dB; test point 5: 23dB; test point 6: 25dB; test point 7: 27dB; test point 8: 30dB;

[0053] Among the 5 test points, the bit error rate of each test point is as follows: test point 1: 0.03%; test point 2: 0.02%; test point 3: 0.04%; test point 4: 0.01%; test point 5: 0.03%.

[0054] Suppose the above microwave network related data is that there are many steep slopes, mountains and valleys in the mine site, such as:

[0055] Steep hillside: Hillside height difference: The height difference of the hillside around the mine site can reach 300 meters; Angle of slope: The average angle of the hillside is between 30 and 45 degrees, and the steepest part may exceed 60 degrees (when the signal propagates from above the hillside to below, it may experience more than 10 dB of attenuation due to the slope reflection and scattering of the hillside, and the signal may produce multiple paths to the receiving antenna, causing multipath interference and time delay spread);

[0056] Mountain: Mountain height: The surrounding mountains generally have an elevation of 1000 to 2000 meters; Distance: The distance between two adjacent mountains can reach more than two kilometers (mountains can limit the propagation range and strength of microwave signals, and the signal may experience more than 20 dB of attenuation when passing through the mountains);

[0057] Canyon: Canyon depth: The depth of the canyon can reach hundreds of meters, and the deepest part may exceed 1000 meters; Width: The width of the canyon varies between 200 to 900 meters (due to the blocking effect of the canyon wall, the signal may experience more than 20 dB of attenuation when propagating from the bottom of the canyon to the top, and in order to provide continuous signal coverage across the canyon, relay equipment or relay antennas may need to be set up on both sides of the canyon);

[0058] The mine site has high annual rainfall, often has snowfall, and morning or heavy fog often occurs: Annual rainfall: According to local weather records, the annual rainfall in the area where the mine site is located is 1500 mm; Snowfall: The typical winter snowfall in this area is 800 mm, mainly concentrated in November to the following March; Fog frequency: Morning or heavy fog is relatively common in this area, with an average of 8 to 12 times per month over the years.

[0059] The above microwave network layout target information is:

[0060] Microwave antennas: Area A: 12 microwave antennas are installed, each with a coverage radius of 3 kilometers; Area B: 9 microwave antennas are set up, each with a coverage radius of 2.5 kilometers; Area C: 15 microwave antennas are installed, each with a coverage radius of 4 kilometers;

[0061] Relay stations: Relay station A: located between area A and area B; Relay station B: located between area B and area C; Relay station C: located between area A and area C;

[0062] Transmission equipment: From relay station A to relay station B: a set of microwave link equipment is used for signal transmission; From relay station B to relay station C: a set of microwave link equipment is used for signal transmission; From relay station A to relay station C: a set of microwave link equipment is used for signal transmission;

[0063] Modem: Each microwave antenna, relay station and transmission equipment is equipped with a modem to realize the functions of signal encoding and decoding.

[0064] Wireless switch: A wireless switch is arranged between relay station A, relay station B and relay station C respectively, for managing and controlling data transmission.

[0065] Through the embodiment, first, for a target microwave network layout task corresponding to a target open-pit mine, target microwave network description data corresponding to the target microwave network layout task and microwave network related data corresponding to the target microwave network layout task are determined, the target microwave network description data includes microwave network current information and microwave network test target information, the microwave network current information includes microwave network test current information and microwave network layout current information, the microwave network test current information is used to reflect the signal test quality of the current microwave network corresponding to the microwave network layout current information, and the microwave network test target information is used to reflect the signal test quality of the improved microwave network; then, the microwave network test target information, the microwave network current information and the microwave network related data are associated and mined to form a microwave network layout vector corresponding to the target microwave network layout task, the microwave network layout vector is used to reflect the semantic features of the microwave network test target information, the microwave network current information and the microwave network related data; finally, the microwave network layout vector is loaded into an updated microwave layout analysis network, and the microwave layout analysis network is used to analyze and generate at least one microwave network layout target information matched with the microwave network test target information, the microwave network layout target information is used to reflect the layout information of the improved microwave network. In the scheme of the application, when generating the microwave network layout target information, not only the microwave network test target information, but also the microwave network test current information and the microwave network layout current information are used, so that the microwave network layout target information is more matched with the microwave network test current information and the microwave network layout current information, and the current microwave network is improved. Therefore, the reliability of the microwave network layout generation is improved, thereby improving the problem of relatively low reliability in the prior art. In addition, the microwave network related data is also used as a basis for analysis, so that the basis for analysis is more sufficient, thereby improving the reliability.

[0066] In order to determine the microwave network layout vector corresponding to the target microwave network layout task according to the microwave network test target information, the microwave network current information and the microwave network related data, in an optional embodiment, the step S202 includes:

[0067] Step S2021, combining the microwave network test current information and the microwave network layout current information in the microwave network current information, and the microwave network test target information to form the to-be-processed sequence data.

[0068] In a specific implementation scenario, the microwave network test current information and the microwave network layout current information in the microwave network current information are combined with the microwave network test target information to form the to-be-processed sequence data, such as: "In 10 test points, the signal strength of each test point is as follows: test point 1: -50 dBm; test point 2: -45 dBm; test point 3: -48 dBm... Microwave antenna: region A: 10 microwave antennas are installed, and each antenna has a coverage radius of 3 kilometers; region B: 8 microwave antennas are set... In 10 test points, the signal strength of each test point is as follows: test point 1: -48 dBm; test point 2: -43 dBm; test point 3: -46 dBm..." to obtain the to-be-processed sequence data.

[0069] Step S2022, mining the first microwave network layout vector corresponding to the target microwave network layout task according to the to-be-processed sequence data.

[0070] Specifically, the to-be-processed sequence data is converted into vector processing to obtain the first microwave network layout vector represented by a vector.

[0071] Step S2023, mining the second microwave network layout vector corresponding to the target microwave network layout task according to the microwave network related data.

[0072] Specifically, the microwave network related data is vectorized to obtain the second microwave network layout vector represented by a vector.

[0073] Step S2024, aggregating the first microwave network layout vector and the second microwave network layout vector to form the microwave network layout vector corresponding to the target microwave network layout task.

[0074] Specifically, the aggregation manner includes directly superimposing or splicing the first microwave network layout vector and the second microwave network layout vector, and can also perform attention mechanism coding and the like.

[0075] In order to obtain the first microwave network layout vector according to the to-be-processed sequence, in an optional implementation manner, the step S2022 includes:

[0076] In step S20221, the data unit features of each data unit included in the to-be-processed sequence data are obtained, and the data unit features of each data unit are combined according to the sequence of each data unit in the to-be-processed sequence data to form a corresponding first local network layout vector.

[0077] In an embodiment, the data unit feature refers to an embedding feature, that is, the embedding network is used for embedding, for example, embedding is performed on "in 10 test points, the signal strength of each test point is as follows: test point 1: -50dBm; test point 2: -45dBm; test point 3: -48dBm... Microwave antenna: region A: 10 microwave antennas are installed, and each antenna has a coverage radius of 3 kilometers; region B: 8 microwave antennas are set... In 10 test points, the signal strength of each test point is as follows: test point 1: -48dBm; test point 2: -43dBm; test point 3: -46dBm...", and the obtained first local network layout vector can be: [0.5, 0.2, 0.8, 0.4, 0.9, 0.1, 0.7, 0.3, 0.6, 0.2,..., 0.4, 0.9, 0.3, 0.8, 0.1, 0.5, 0.7, 0.2, 0.6, 0.9,..., 0.4, 0.3, 0.1, 0.8, 0.6, 0.5, 0.2, 0.9, 0.7, 0.4, 0.3].

[0078] In step S20222, for each data unit in the to-be-processed sequence data, the segment flag data of the sequence segment to which the data unit belongs is obtained, the granularity of the data unit is a word, a phrase or a sentence, and the sequence segment is the microwave network test current information, the microwave network layout current information or the microwave network test target information in the current information of the microwave network.

[0079] In an embodiment, the corresponding segment flag data can be 1 if it belongs to the microwave network test current information, 2 if it belongs to the microwave network layout current information, and 3 if it belongs to the microwave network test target information.

[0080] In step S20223, the segment flag data corresponding to each data unit is combined according to the sequence of each data unit in the to-be-processed sequence data to form a second local network layout vector.

[0081] In an embodiment, the segment mark data corresponding to each data unit is combined according to the sequence of each data unit in the to-be-processed sequence data, and the second local network layout vector is: [1, 1, 1, 1, 1, 1, 1, …, 2, 2, 2, 2, 2, 2, 2, …, 3, 3, 3, 3, 3, 3, 3].

[0082] In step S20224, coordinate mark data of each data unit in the to-be-processed sequence data is obtained.

[0083] In an embodiment, the coordinate mark data corresponding to the first data unit can be 0, the coordinate mark data corresponding to the second data unit can be 1, and the coordinate mark data corresponding to the third data unit can be 2.

[0084] In step S20225, the coordinate mark data corresponding to each data unit is combined according to the sequence of each data unit in the to-be-processed sequence data to form a third local network layout vector.

[0085] Specifically, the coordinate mark data corresponding to each data unit is combined according to the sequence of each data unit in the to-be-processed sequence data, and the third local network layout vector is: [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, …].

[0086] In step S20226, the first local network layout vector, the second local network layout vector, and the third local network layout vector are aggregated to form a first microwave network layout vector corresponding to the target microwave network layout task.

[0087] Specifically, the first local network layout vector, the second local network layout vector, and the third local network layout vector are aggregated, including splicing or superimposing, to form the first microwave network layout vector corresponding to the target microwave network layout task.

[0088] In order to determine the second microwave network layout vector according to the target microwave network layout task, in an optional embodiment, the microwave network related data further includes microwave network environment data and team description data of an improvement team of the target microwave network layout task, the improvement team includes improvement personnel and improvement equipment, and the step S2023 includes:

[0089] In step S20231, microwave network related vectors of the microwave network environment data and microwave network related vectors of the team description data are mined.

[0090] Specifically, the above-mentioned improvement team includes improvement personnel and improvement equipment. The improvement personnel includes, for example, a communication engineer responsible for implementing and managing microwave network improvement projects, including installation, commissioning and maintenance of microwave antennas and transmission equipment; a civil engineer who will participate in site survey, design and construction work if it is necessary to change the location of microwave antennas or build new communication towers; a power engineer who ensures that microwave network equipment can obtain stable power supply, which may require upgrading or modification of the power system; and a surveyor who performs tasks such as topographic survey, signal coverage test and data collection during the improvement process to ensure the effectiveness of the new layout. The improvement equipment includes, for example, drilling equipment for drilling the ground or rock to install the supports or foundations required by microwave antennas or transmission equipment; cranes or hoists for installing and unloading microwave antennas, communication towers or other large equipment; cable laying equipment including trenchers, cable rollers, etc. for laying and maintaining cables required by microwave networks; and test instruments such as spectrum analyzers, network analyzers, etc. for testing and commissioning the quality and performance of microwave signals.

[0091] It should be noted that the above team description data can be used to characterize the scale of microwave network improvement, for example, when the scale is small, the amount of improvement in the modification project can be smaller, so that the generated microwave network layout target information is more reliable.

[0092] The above-mentioned microwave network environment data and the above-mentioned team description data are converted into vectors to represent them in a vectorized manner, such as embedding processing, to obtain corresponding microwave network related vectors.

[0093] In step S20232, the microwave network related vectors of the microwave network environment data and the team description data included in the above-mentioned microwave network related data are aggregated to form a second microwave network layout vector corresponding to the above-mentioned target microwave network layout task.

[0094] Specifically, the microwave network related vectors of the microwave network environment data and the team description data included in the above-mentioned microwave network related data are aggregated, such as splicing or superimposing, to form a second microwave network layout vector corresponding to the above-mentioned target microwave network layout task.

[0095] In order to obtain the above-mentioned microwave network layout target information, in an optional implementation, the above-mentioned step S203 includes:

[0096] In step S2031, the above-mentioned microwave network layout vector is loaded into the above-mentioned microwave layout analysis network, and at least one first undetermined data unit corresponding to the above-mentioned microwave network test target information is analyzed, and the granularity of the above-mentioned undetermined data unit is word, phrase or sentence.

[0097] In an embodiment, the microwave network test target information is "in 10 test points, the signal strength of each test point is as follows: test point 1: -48dBm; test point 2: -43dBm; test point 3: -46dBm; test point 4: -50dBm; test point 5: -52dBm; test point 6: -47dBm; test point 7: -45dBm; test point 8: -49dBm; test point 9: -51dBm; test point 10: -46dBm; in 8 test points, the signal-to-noise ratio of each test point is as follows: test point 1: 28dB; test point 2: 26dB; test point 3: 29dB; test point 4: 24dB; test point 5: 23dB; test point 6: 25dB; test point 7: 27dB; test point 8: 30dB; in 5 test points, the bit error rate of each test point is as follows: test point 1: 0.03%; test point 2: 0.02%; test point 3: 0.04%; test point 4: 0.01%; test point 5: 0.03%".

[0098] The first pending data unit analyzed from the microwave network test target information can include "microwave", "miniature", and "network".

[0099] In step S2032, each of the first pending data units is combined at the end of the microwave network test target information, and each of the combined extended data is taken as an extended microwave network test target information to form at least one corresponding extended microwave network test target information, and in the process of forming the microwave network layout vector corresponding to the target microwave network layout task, the microwave network test target information is arranged at the end in the formed to-be-processed sequence data.

[0100] In an embodiment, a "microwave" can be added to the tail of the microwave network test target information above, to obtain a first extended microwave network test target information, i.e., "In 10 test points, the signal strength of each test point is as follows: test point 1: -48dBm; test point 2: -43dBm; test point 3: -46dBm; test point 4: -50dBm; test point 5: -52dBm; test point 6: -47dBm; test point 7: -45dBm; test point 8: -49dBm; test point 9: -51dBm; test point 10: -46dBm; In 8 test points, the signal-to-noise ratio of each test point is as follows: test point 1: 28dB; test point 2: 26dB; test point 3: 29dB; test point 4: 24dB; test point 5: 23dB; test point 6: 25dB; test point 7: 27dB; test point 8: 30dB; In 5 test points, the bit error rate of each test point is as follows: test point 1: 0.03%; test point 2: 0.02%; test point 3: 0.04%; test point 4: 0.01%; test point 5: 0.03%, microwave".

[0101] Similarly, a "miniature" is added to the tail of the microwave network test target information above, to obtain a second extended microwave network test target information, and a "network" is added to the tail of the microwave network test target information above, to obtain a third extended microwave network test target information.

[0102] In step S2033, for each of the extended microwave network test target information, an extended microwave network layout vector corresponding to each of the extended microwave network test target information is determined according to the current microwave network information and the microwave network related data.

[0103] Specifically, in the foregoing steps, the microwave network test target information is replaced with the extended microwave network test target information, and then the same processing is performed to obtain the corresponding extended microwave network layout vector.

[0104] In step S2034, each of the extended microwave network layout vectors is loaded into the microwave layout analysis network to analyze at least one second pending data unit corresponding thereto.

[0105] Specifically, each of the extended microwave network layout vectors is loaded into the microwave layout analysis network to analyze at least one second pending data unit corresponding thereto, as described above.

[0106] In step S2035, when the second pending data unit belongs to an end marker data, at least one microwave network layout target information matching the microwave network test target information is formed based on the first pending data unit and the second pending data unit.

[0107] Specifically, when the second pending data unit belongs to the end mark data (such as a period or other pre-set end representation data, and the specific end representation data can be determined according to the end representation data in the label during the process of performing the corresponding network update), at least one microwave network layout target information matched with the microwave network test target information is formed by combining the first pending data unit and the second pending data unit. In addition, when the second pending data unit does not belong to the end mark data, the third pending data unit, the fourth pending data unit, etc. can be sequentially determined according to the foregoing processing logic until the end mark data is determined. In addition, it should be noted that, in order to avoid too many microwave network layout target information generated finally, the number of pending data units generated in the process of generating the pending data units can be reduced. For example, the first pending data unit can be 3 or 5. For each of the 3 or 5 extended microwave network layout vectors corresponding to the first pending data unit, only one pending data unit can be generated, so that the total number of the second pending data units is also 3 or 5, the total number of the third pending data units is also 3 or 5, and there is a one-to-one correspondence, so that 3 or 5 microwave network layout target information can be formed by combination.

[0108] Similarly, when the second pending data unit does not belong to the end marker data, each second pending data unit is combined at the tail of the extended microwave network test target information, and each combined extended data is taken as a second-level extended microwave network test target information to form at least one second-level extended microwave network test target information corresponding to each extended microwave network layout vector, the number of at least one second pending data unit corresponding to the extended microwave network layout vector is equal to the number of at least one first pending data unit, thus the total number of second-level extended microwave network test target information is the square of the number of at least one first pending data unit, for example, when the number of at least one first pending data unit is equal to 3, the total number of second-level extended microwave network test target information is the square of 3, the total number of third-level extended microwave network test target information is the cube of 3, and so on. Alternatively, in order to avoid too many extended microwave network test target information after multiple levels of expansion, the number can be reduced when generating a subsequent pending data unit during the expansion process, for example, the number of generated pending data units can be 3, 3, 2, 1, 1, 1, 1, 1, and so on, or during the expansion process, after reaching a certain value, the target level of the extended microwave network test target information is subjected to semantic detection, for example, semantic fluency detection, and the extended microwave network test target information with lower semantic fluency is discarded.

[0109] For each second-level extended microwave network test target information, a second-level extended microwave network layout vector corresponding to each second-level extended microwave network test target information is determined according to the current microwave network information and the microwave network related data.

[0110] Each second-level extended microwave network layout vector is loaded into the microwave layout analysis network to analyze at least one third pending data unit, and so on, to obtain a fourth pending data unit, a fifth pending data unit, and so on, until the end marker data is obtained.

[0111] In order to obtain the first pending data unit, in an optional embodiment, the step S2031 comprises:

[0112] In step S20311, the microwave network layout vector is loaded into the microwave layout analysis network to analyze a plurality of microwave layout analysis data corresponding to the microwave network test target information, each microwave layout analysis data comprises an original data unit and a prediction probability of the original data unit.

[0113] Specifically, the number of the above-mentioned microwave layout analysis data is not limited, and can be configured according to actual needs.

[0114] Step S20312, according to the size relationship of the corresponding prediction probability, the plurality of the above-mentioned original data units are sorted to form a corresponding original data unit sequence.

[0115] Specifically, according to the size relationship of the corresponding prediction probability, the plurality of the above-mentioned original data units are sorted to form a corresponding original data unit sequence, such as original data unit 1 (corresponding prediction probability is 0.50), original data unit 3 (corresponding prediction probability is 0.46), original data unit 4 (corresponding prediction probability is 0.42), original data unit 2 (corresponding prediction probability is 0.26).

[0116] Step S20313, in the above-mentioned original data unit sequence, according to the size relationship of the corresponding prediction probability from large to small in turn, each original data unit is traversed, and the corresponding prediction probability of each original data unit traversed is accumulated.

[0117] Specifically, in the above-mentioned original data unit sequence, according to the size relationship of the corresponding prediction probability from large to small in turn, each original data unit is traversed, and the corresponding prediction probability of each original data unit traversed is accumulated.

[0118] Step S20314, after each accumulation, the size relationship between the current obtained accumulation result and the preset parameter is judged, and in the case that the current obtained accumulation result is less than the above-mentioned preset parameter, the next original data unit is continued to be traversed, or in the case that the current obtained accumulation result is greater than or equal to the above-mentioned preset parameter, each original data unit traversed is taken as at least one first undetermined data unit corresponding to the above-mentioned microwave network test target information.

[0119] Specifically, the specific value of the above-mentioned preset parameter is not limited, and can be configured according to actual needs, such as 0.8, so that the original data unit 1 is traversed first, the corresponding prediction probability is equal to 0.50, which is less than the above-mentioned preset parameter, and the traversal is continued, and the original data unit 3 is traversed, the corresponding prediction probability is equal to 0.46, and the sum value of the prediction probability corresponding to the original data unit 1 is equal to 0.96, which is greater than the preset parameter, so that the traversal can be stopped, and each original data unit traversed is taken as at least one first undetermined data unit corresponding to the above-mentioned microwave network test target information, that is, the first undetermined data unit is two, which are original data unit 1 and original data unit 3.

[0120] In order to obtain the extended microwave network layout vector, in an optional implementation, the step S2033 comprises:

[0121] Step S20331, combining the microwave network test current information and the microwave network layout current information in the microwave network current information, and the extended microwave network test target information, to form an extended to-be-processed sequence data.

[0122] Specifically, the microwave network test current information and the microwave network layout current information in the microwave network current information are combined with the extended microwave network test target information to form the extended to-be-processed sequence data, which is the same as the step of obtaining the to-be-processed sequence data.

[0123] Step S20332, mining an extended first microwave network layout vector corresponding to the target microwave network layout task according to the extended to-be-processed sequence data.

[0124] Specifically, the extended first microwave network layout vector corresponding to the target microwave network layout task is mined according to the extended to-be-processed sequence data, which is the same as the step of obtaining the first microwave network layout vector.

[0125] Step S20333, mining a second microwave network layout vector corresponding to the target microwave network layout task according to the microwave network related data.

[0126] Specifically, the second microwave network layout vector corresponding to the target microwave network layout task is mined according to the microwave network related data, which is the same as the step of obtaining the second microwave network layout vector.

[0127] Step S20334, aggregating the extended first microwave network layout vector and the second microwave network layout vector to form an extended microwave network layout vector corresponding to the target microwave network layout task.

[0128] Specifically, the extended first microwave network layout vector and the second microwave network layout vector are aggregated to form the extended microwave network layout vector corresponding to the target microwave network layout task, which is the same as the step of obtaining the microwave network layout vector.

[0129] In order to update the microwave layout analysis network, in an optional implementation, the step S204 comprises:

[0130] Step S2041, determine an example information cluster, the example information cluster includes a plurality of example information, each example information includes example microwave network description data corresponding to an example microwave network layout task, example microwave network layout target information and example microwave network related data, and the example microwave network layout target information is the improved layout information of the example microwave network corresponding to the example microwave network description data.

[0131] Specifically, determine an example information cluster, the example information cluster includes a plurality of example information, each example information includes example microwave network description data (corresponding to the aforementioned microwave network description data) corresponding to an example microwave network layout task (corresponding to the aforementioned target microwave network layout task), example microwave network layout target information (i.e. actual improved microwave network layout information, for supervised learning, it can be understood that when supervised learning is performed, a plurality of example microwave network layout target information can be configured, i.e. matching example microwave network layout target information and non-matching example microwave network layout target information, as positive examples and negative examples, i.e. positive samples and negative samples, such as based on example microwave network layout target information matching the target network quality and having a small scale of change, forming a positive example, based on example microwave network layout target information not matching the target network quality or matching the target network quality but having a large scale of change, forming a negative example, in this way, the microwave network layout target information generated by the updated microwave layout analysis network has a smaller change compared to the current microwave network layout information) and example microwave network related data (corresponding to the aforementioned microwave network related data), and the example microwave network layout target information is the improved layout information of the example microwave network corresponding to the example microwave network description data.

[0132] Step S2042, for each example information, according to the example microwave network description data and the example microwave network related data included in the example information, associate and mine out the example microwave network layout vector corresponding to the example microwave network description data;

[0133] Specifically, for each example information, according to the example microwave network description data and the example microwave network related data included in the example information, associate and mine out the example microwave network layout vector corresponding to the example microwave network description data, which is the same as the step of obtaining the microwave network layout vector.

[0134] Step S2043, according to the example microwave network layout vector and the example microwave network layout target information corresponding to each of the example information, update the candidate microwave layout analysis network as follows:

[0135] For each of the above example information, load the example microwave network layout vector corresponding to the above example information into the above candidate microwave layout analysis network, and use the above candidate microwave layout analysis network to analyze and generate at least one estimated microwave network layout target information corresponding to the above example microwave network layout vector;

[0136] Specifically, for each of the above example information, load the example microwave network layout vector corresponding to the above example information into the above candidate microwave layout analysis network, and use the above candidate microwave layout analysis network to analyze and generate at least one estimated microwave network layout target information corresponding to the above example microwave network layout vector, which is the same as the step of obtaining the microwave network layout target information.

[0137] Step S2044, according to the at least one estimated microwave network layout target information corresponding to each of the above example information and the example microwave network layout target information, calculate the network update error corresponding to the above candidate microwave layout analysis network;

[0138] Specifically, the network update error is used to reflect the difference between the estimated microwave network layout target information and the example microwave network layout target information.

[0139] Step S2045, when the network update error is less than a preset error, the current candidate microwave layout analysis network is taken as the updated microwave layout analysis network;

[0140] Specifically, the preset error can be configured according to actual needs, and the network update error is less than the preset error, which indicates that the error of the current candidate microwave layout analysis network has converged, and the precision of the analysis capability of the network is relatively high, and there is no need to update.

[0141] Step S2046, when the network update error is greater than or equal to the preset error, update the network parameters of the above candidate microwave layout analysis network according to the network update error, and continue to update the current updated candidate microwave layout analysis network according to the example microwave network layout vector corresponding to each of the above example information and the example microwave network layout target information.

[0142] Specifically, the network update error is greater than or equal to the preset error, which indicates that the error of the current candidate microwave layout analysis network has not converged, and the precision of the analysis capability of the network is relatively low, and needs to be updated.

[0143] In a specific embodiment, the microwave layout analysis network can be a convolutional neural network, which can specifically include:

[0144] Input layer: load the microwave network layout vector as input;

[0145] Convolutional layer: extract spatial features from input data through a series of convolution operations, each using a set of convolution kernels to scan the input data and produce a series of feature vectors that capture spatial information at different positions and scales;

[0146] Pooling layer: downsample the feature vectors output by the convolutional layer to reduce data dimensionality, common pooling operations include max pooling or average pooling, which help to preserve important features and reduce computational complexity;

[0147] Fully connected layer: flatten the feature vectors output by the pooling layer into a vector and perform non-linear mapping and processing through multiple fully connected layers, which can learn more advanced feature representations and further extract semantic information from microwave layout;

[0148] Output layer: the output layer can be designed as a classification layer to output each original data unit and its predicted probability, including functions such as softmax.

[0149] In order to obtain the final microwave network layout target information, in an optional implementation, the method further comprises:

[0150] Step S301, when the number of microwave network layout target information matching the microwave network test target information is equal to 1, the microwave network layout target information is taken as the final output data of the target microwave network layout task;

[0151] Specifically, when the number of microwave network layout target information matching the microwave network test target information is equal to 1, it is determined that the required microwave network layout target information is unique, and the result is output.

[0152] Step S302, when the number of microwave network layout target information matching the microwave network test target information is greater than 1, the similarity between each microwave network layout target information and the current microwave network layout information is calculated respectively, and the microwave network layout target information with the maximum similarity is taken as the final output data of the target microwave network layout task.

[0153] Specifically, when the number of the microwave network layout target information matching the microwave network test target information is greater than 1 (i.e. multiple pieces of microwave network layout target information are generated), the similarity between each piece of microwave network layout target information and the microwave network layout current information is calculated (such as calculating the text similarity or calculating the cosine similarity between vectors after vectorization processing, etc.), and the piece of microwave network layout target information with the maximum similarity is taken as the final output data of the target microwave network layout task. Thus, since the similarity between the microwave network layout target information taken as the final output data of the target microwave network layout task and the microwave network layout current information is the maximum, the change range is the smallest when the microwave network is improved based on the microwave network layout target information, i.e. the engineering scale of the change is the smallest to a certain extent, so that the reliability of the information generation can be further improved, and the signal quality requirement corresponding to the microwave network test target information can be met.

[0154] It should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a set of computer executable instructions, and although the logical order is shown in the flowchart, in some cases, the steps shown or described herein can be executed in an order different from that shown.

[0155] The embodiment of the present application further provides an information generation device based on microwave network test of super large open-pit mine. It should be noted that the information generation device based on microwave network test of super large open-pit mine of the embodiment of the present application can be used to execute the information generation method based on microwave network test of super large open-pit mine provided by the embodiment of the present application. The device is used to realize the above-mentioned embodiment and preferred embodiment, and will not be described here. As used below, the term "module" can be a combination of software and / or hardware that realizes a predetermined function. Although the device described in the following embodiment is preferably realized in software, the realization of hardware or a combination of software and hardware is also possible and is conceived.

[0156] The information generation device based on microwave network test of super large open-pit mine provided by the embodiment of the present application is described below.

[0157] Figure 3 is a structural block diagram of the information generation device based on microwave network test of super large open-pit mine according to the embodiment of the present application. As shown in Figure 3 , the device comprises:

[0158] The microwave network data determination module 10 is configured to determine, for a target microwave network layout task corresponding to a target strip mine, target microwave network description data corresponding to the target microwave network layout task and microwave network related data corresponding to the target microwave network layout task, wherein the target microwave network description data comprises microwave network current information and microwave network test target information, the microwave network current information comprises microwave network test current information and microwave network layout current information, the microwave network test current information is used to reflect signal test quality of a current microwave network corresponding to the microwave network layout current information, and the microwave network test target information is used to reflect signal test quality of an improved microwave network.

[0159] The microwave network data mining module 20 is configured to perform association mining on the microwave network test target information, the microwave network current information and the microwave network related data to form a microwave network layout vector corresponding to the target microwave network layout task, wherein the microwave network layout vector is used to reflect semantic features of the microwave network test target information, the microwave network current information and the microwave network related data.

[0160] The microwave network layout analysis module 30 is configured to load the microwave network layout vector into an updated microwave layout analysis network, and analyze at least one microwave network layout target information matched with the microwave network test target information by using the microwave layout analysis network, wherein the microwave network layout target information is used to reflect layout information of the improved microwave network.

[0161] Through the above embodiment, the microwave network data determination module determines the target microwave network layout task corresponding to the target strip mine, determines the target microwave network description data corresponding to the target microwave network layout task and the microwave network related data corresponding to the target microwave network layout task, the target microwave network description data includes microwave network current information and microwave network test target information, the microwave network current information includes microwave network test current information and microwave network layout current information, the microwave network test current information is used to reflect the signal test quality of the current microwave network corresponding to the microwave network layout current information, and the microwave network test target information is used to reflect the signal test quality of the improved microwave network. The microwave network data mining module associates and mines the microwave network test target information, the microwave network current information and the microwave network related data to form a microwave network layout vector corresponding to the target microwave network layout task, and the microwave network layout vector is used to reflect the semantic features of the microwave network test target information, the microwave network current information and the microwave network related data. The microwave network layout analysis module loads the microwave network layout vector into the updated microwave layout analysis network, analyzes at least one microwave network layout target information matched with the microwave network test target information by using the microwave layout analysis network, and the microwave network layout target information is used to reflect the layout information of the improved microwave network. In the scheme of the application, when generating the microwave network layout target information, not only the microwave network test target information, but also the microwave network test current information and the microwave network layout current information are used, so that the microwave network layout target information is more matched with the microwave network test current information and the microwave network layout current information, and the current microwave network is improved. Therefore, the reliability of the microwave network layout generation is improved, thereby improving the problem of relatively low reliability in the prior art. In addition, the microwave network related data is also used, so that the basis for analysis is more sufficient to improve the reliability.

[0162] The above information generation device based on the microwave network test of the super large strip mine includes a processor and a memory, and the units and the like are stored in the memory as program units. The corresponding functions are realized by the processor executing the program units stored in the memory. The modules are located in the same processor; or, the modules are located in different processors in any combination.

[0163] The processor includes a core, and the core retrieves the corresponding program unit from the memory. The core can be set to one or more, and the reliability of the network layout generation is improved by adjusting the core parameters.

[0164] The memory can include non-persistent memory in a computer readable medium, random access memory (RAM) and / or non-volatile memory, such as read only memory (ROM) or flash memory, and the memory includes at least one memory chip.

[0165] The embodiment of the present application provides a computer readable storage medium, the computer readable storage medium comprises a stored program, wherein the program controls a device where the computer readable storage medium is located to execute the information generation method based on microwave network testing of a super large open-pit mine when the program is running.

[0166] The embodiment of the present application provides a processor, the processor is used for running a program, wherein the program executes the information generation method based on microwave network testing of a super large open-pit mine when the program is running.

[0167] The embodiment of the present application provides an information generation system based on microwave network testing of a super large open-pit mine, the information generation system based on microwave network testing of a super large open-pit mine comprises a processor, a memory and a program stored in the memory and capable of running on the processor, and the processor executes the program to realize at least the information generation step based on microwave network testing of a super large open-pit mine.

[0168] As shown in Figure 4 The embodiment of the present application provides an information generation system based on microwave network testing of a super large open-pit mine. The structure block diagram is as shown in Figure 4 In detail, the memory and the processor are directly or indirectly electrically connected to realize data transmission or interaction. For example, the electrically connected can be realized through one or more communication buses or signal lines. The memory can store at least one software function module (i.e. computer program) in the form of software or firmware. The processor can be used to execute the executable computer program stored in the memory, so as to realize the information generation method based on microwave network testing of a super large open-pit mine provided by the embodiment of the present application.

[0169] The embodiment of the present application also provides a computer program product, when executed on a data processing device, is suitable for executing the program initialized with at least the information generation step based on microwave network testing of a super large open-pit mine.

[0170] It should be apparent to those skilled in the art that the modules or steps of the application described above can be implemented with a general purpose computer, and can be centralized in a single computer or distributed among a network of computers, and can be implemented with program code executable by a computer, and thus can be stored in a storage device and executed by a computer, and in some cases, the steps shown or described can be executed in a different order than shown or described, or can be implemented as separate integrated circuit modules or as a single integrated circuit module, and thus the application is not limited to any particular combination of hardware and software.

[0171] Those skilled in the art will appreciate that embodiments of the application can be devised for a method, a system, or a computer program product. Accordingly, the application can be embodied in the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the application can be in the form of a computer program product on one or more computer-usable storage media (including, but not limited to, disk memory, CD-ROMs, optical storage media, etc.) embodying computer readable program code.

[0172] The present application is described in reference to the flowchart illustrations and / or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the application. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart illustrations and / or block diagrams. Figure 1 one or more functions specified in the flowchart illustrations and / or block diagrams. Figure 1 one or more functions specified in the flowchart illustrations and / or block diagrams.

[0173] These computer program instructions can also be stored in a computer- readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instructions which implement the functions specified in the flowchart illustrations and / or block diagrams. Figure 1 one or more functions specified in the flowchart illustrations and / or block diagrams. Figure 1 one or more functions specified in the flowchart illustrations and / or block diagrams.

[0174] These computer program instructions can also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer-implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart illustrations and / or block diagrams.Figure 1 one or more processes and / or functions specified in one or more blocks Figure 1 one or more processes and / or functions specified in one or more blocks

[0175] In a typical configuration, a computing device includes one or more processors (CPUs), input / output interfaces, network interfaces, and memory.

[0176] The memory can include non-persistent memory and / or volatile memory, such as random access memory (RAM) and / or cache memory, non-volatile memory, such as read-only memory (ROM), EPROM, and / or flash memory, etc. The memory is an example of computer readable media.

[0177] Computer readable media includes permanent and non-permanent, removable and non-removable media implemented in any method or technology for storage of information such as computer readable instructions, data structures, program modules or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, compact disc read-only memory (CD-ROM), digital versatile disc (DVD), or other optical storage, magnetic cassette, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other non-transmission medium that can be used to store information accessible to a computing device. According to the definition herein, computer readable media does not include transitory media, such as modulated data signals and carrier waves.

[0178] It should also be noted that the terms "comprising", "containing", or any other variant thereof, are intended to cover non-exclusive inclusion, so that processes, methods, articles or devices that include a series of elements not only include those elements, but also include other elements not explicitly listed or inherent to such processes, methods, articles or devices. Without more limitations, the element defined by the statement "comprising a" does not exclude the presence of additional identical elements in the process, method, article or device including the element.

[0179] From the above description, it can be seen that the above-mentioned embodiments of the present application achieve the following technical effects:

[0180] 1) The information generation method based on microwave network test of super large open-pit mine in the application, first, for the target microwave network layout task corresponding to the target open-pit mine, the target microwave network description data corresponding to the target microwave network layout task and the microwave network related data corresponding to the target microwave network layout task are determined, the target microwave network description data includes microwave network current information and microwave network test target information, the microwave network current information includes microwave network test current information and microwave network layout current information, the microwave network test current information is used to reflect the signal test quality of the current microwave network corresponding to the microwave network layout current information, the microwave network test target information is used to reflect the signal test quality of the improved microwave network; Then, the microwave network test target information, the microwave network current information and the microwave network related data are associated and mined to form the microwave network layout vector corresponding to the target microwave network layout task, the microwave network layout vector is used to reflect the semantic characteristics of the microwave network test target information, the microwave network current information and the microwave network related data; Finally, the microwave network layout vector is loaded into the microwave layout analysis network which has been updated, and the microwave layout analysis network is used to analyze and generate at least one microwave network layout target information matched with the microwave network test target information, the microwave network layout target information is used to reflect the layout information of the improved microwave network. In the scheme of the application, when generating the microwave network layout target information, not only the microwave network test target information will be used, but also the microwave network test current information and the microwave network layout current information, so that the microwave network layout target information is more matched with the microwave network test current information and the microwave network layout current information, which is convenient for improving the current microwave network. Therefore, the reliability of microwave network layout generation is improved, thereby improving the problem of relatively low reliability in the prior art. In addition, since the microwave network related data is also used, the basis for analysis is more sufficient to improve the reliability.

[0181] 2), the information generation device based on the microwave network test of the super large open-pit mine of the application, the microwave network data determination module determines the target microwave network description data corresponding to the target microwave network layout task of the target open-pit mine and the microwave network related data corresponding to the target microwave network layout task, the target microwave network description data includes microwave network current information and microwave network test target information, the microwave network current information includes microwave network test current information and microwave network layout current information, the microwave network test current information is used to reflect the signal test quality of the current microwave network corresponding to the microwave network layout current information, the microwave network test target information is used to reflect the signal test quality of the improved microwave network; the microwave network data mining module associates and mines the microwave network test target information, the microwave network current information and the microwave network related data to form the microwave network layout vector corresponding to the target microwave network layout task, the microwave network layout vector is used to reflect the semantic characteristics of the microwave network test target information, the microwave network current information and the microwave network related data; the microwave network layout analysis module loads the microwave network layout vector into the microwave layout analysis network which has been updated, and uses the microwave layout analysis network to analyze and generate at least one microwave network layout target information matched with the microwave network test target information, the microwave network layout target information is used to reflect the layout information of the improved microwave network. In the scheme of the application, when generating the microwave network layout target information, not only the microwave network test target information will be used, but also the microwave network test current information and the microwave network layout current information will be used, so that the microwave network layout target information is more matched with the microwave network test current information and the microwave network layout current information, which is convenient for improving the current microwave network. Therefore, the reliability of the microwave network layout generation is improved, thereby improving the problem of relatively low reliability in the prior art. In addition, since the microwave network related data is also used, the basis for analysis is more sufficient to improve the reliability.

[0182] The above only describes the preferred embodiments of the application and is not intended to limit the application. Those skilled in the art can make various modifications and changes to the application. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the application shall be included in the protection scope of the application.

Claims

1. A method for generating information based on microwave network testing in a super large open-pit mine, characterized in that, The method comprises the steps of: For a target microwave network layout task corresponding to a target open-pit mine, determining target microwave network description data corresponding to the target microwave network layout task and microwave network related data corresponding to the target microwave network layout task, wherein the target microwave network description data comprises microwave network current information and microwave network test target information, the microwave network current information comprises microwave network test current information and microwave network layout current information, the microwave network test current information is used to reflect signal test quality of a current microwave network corresponding to the microwave network layout current information, and the microwave network test target information is used to reflect signal test quality of an improved microwave network; Correlatively mining the microwave network test target information, the microwave network current information and the microwave network related data to form a microwave network layout vector corresponding to the target microwave network layout task, wherein the microwave network layout vector is used to reflect semantic features of the microwave network test target information, the microwave network current information and the microwave network related data; Loading the microwave network layout vector into an updated microwave layout analysis network, and using the microwave layout analysis network to analyze and generate at least one piece of microwave network layout target information matched with the microwave network test target information, wherein the microwave network layout target information is used to reflect layout information of the improved microwave network, The microwave network related data further comprises microwave network environment data and team description data of an improvement team of the target microwave network layout task, and the improvement team comprises improvement personnel and improvement equipment.

2. The method of claim 1, wherein, Correlatively mining the microwave network test target information, the microwave network current information and the microwave network related data to form a microwave network layout vector corresponding to the target microwave network layout task, comprises: Combining the microwave network test current information and the microwave network layout current information in the microwave network current information, the microwave network test target information to form to-be-processed sequence data; According to the to-be-processed sequence data, mining a first microwave network layout vector corresponding to the target microwave network layout task; According to the microwave network related data, mining a second microwave network layout vector corresponding to the target microwave network layout task; Aggregating the first microwave network layout vector and the second microwave network layout vector to form the microwave network layout vector corresponding to the target microwave network layout task.

3. The method of claim 2, wherein, According to the microwave network related data, mining a second microwave network layout vector corresponding to the target microwave network layout task, comprises: Mining a microwave network related vector of the microwave network environment data and a microwave network related vector of the team description data; Aggregating the microwave network related vectors of the microwave network environment data and the team description data included in the microwave network related data to form the second microwave network layout vector corresponding to the target microwave network layout task.

4. The method of claim 2, wherein, According to the to-be-processed sequence data, mining a first microwave network layout vector corresponding to the target microwave network layout task, comprises: Obtaining data unit features of each data unit included in the to-be-processed sequence data, and combining the data unit features of the data units according to the sequence of the data units in the to-be-processed sequence data to form a corresponding first local network layout vector; For each data unit in the to-be-processed sequence data, obtaining the segment marker data of the sequence segment to which the data unit belongs, the granularity of the data unit being a word, a phrase, or a sentence, and the sequence segment being the microwave network test current information, the microwave network layout current information, or the microwave network test target information in the microwave network current information; Combining the segment marker data corresponding to the data units according to the sequence of the data units in the to-be-processed sequence data to form a second local network layout vector; Obtaining coordinate marker data of the data units in the to-be-processed sequence data; Combining the coordinate marker data corresponding to the data units according to the sequence of the data units in the to-be-processed sequence data to form a third local network layout vector; Aggregating the first local network layout vector, the second local network layout vector, and the third local network layout vector to form a first microwave network layout vector corresponding to the target microwave network layout task.

5. The method of claim 1, wherein, Loading the microwave network layout vector into the updated microwave layout analysis network, and using the microwave layout analysis network to analyze and generate at least one microwave network layout target information matching the microwave network test target information, including: Loading the microwave network layout vector into the microwave layout analysis network to analyze at least one first undetermined data unit corresponding to the microwave network test target information, the granularity of the undetermined data unit being a word, a phrase, or a sentence; Combining each first undetermined data unit at the tail of the microwave network test target information, and taking each expanded data after combination as an expanded microwave network test target information to form at least one expanded microwave network test target information, in which the microwave network test target information is arranged at the end in the to-be-processed sequence data formed in the process of association mining to form the microwave network layout vector corresponding to the target microwave network layout task; For each expanded microwave network test target information, determining an expanded microwave network layout vector corresponding to each expanded microwave network test target information according to the microwave network current information and the microwave network related data; Loading each expanded microwave network layout vector into the microwave layout analysis network to analyze at least one second undetermined data unit corresponding to each expanded microwave network layout vector; When the second undetermined data unit belongs to an end marker data, combining the first undetermined data unit and the second undetermined data unit to form at least one microwave network layout target information matching the microwave network test target information.

6. The method of claim 5, wherein, Loading the microwave network layout vector into the microwave layout analysis network, and analyzing at least one first undetermined data unit corresponding to the microwave network test target information, including: Loading the microwave network layout vector into the microwave layout analysis network, and analyzing a plurality of microwave layout analysis data corresponding to the microwave network test target information, each of the microwave layout analysis data including an original data unit and a prediction probability of the original data unit; According to the size relationship of the corresponding prediction probability, a plurality of original data units are sorted to form a corresponding original data unit sequence; In the original data unit sequence, each original data unit is sequentially traversed in the order of the corresponding prediction probability from large to small, and the prediction probability of each original data unit traversed is accumulated; After each accumulation, the size relationship between the current accumulated result and the preset parameter is judged, and in the case that the current accumulated result is less than the preset parameter, the next original data unit is continuously traversed, or in the case that the current accumulated result is greater than or equal to the preset parameter, each original data unit traversed is taken as at least one first undetermined data unit corresponding to the microwave network test target information.

7. The method of claim 5, wherein, For each of the extended microwave network test target information, according to the microwave network current information and the microwave network related data, an extended microwave network layout vector corresponding to each of the extended microwave network test target information is determined, including: Combining the microwave network test current information and the microwave network layout current information in the microwave network current information, the extended microwave network test target information, and forming an extended to-be-processed sequence data; According to the extended to-be-processed sequence data, an extended first microwave network layout vector corresponding to the target microwave network layout task is mined; According to the microwave network related data, a second microwave network layout vector corresponding to the target microwave network layout task is mined; The extended first microwave network layout vector and the second microwave network layout vector are aggregated to form an extended microwave network layout vector corresponding to the target microwave network layout task.

8. The method of claim 5, wherein, The network updating process of the microwave layout analysis network, including: Determine the example information cluster, the example information cluster includes a plurality of example information, each example information includes an example microwave network description data, an example microwave network layout target information and an example microwave network related data corresponding to an example microwave network layout task, the example microwave network layout target information is the layout information of the improved example microwave network corresponding to the example microwave network description data; For each example information, according to the example microwave network description data and the example microwave network related data included in the example information, the example microwave network layout vector corresponding to the example microwave network description data is associatedly mined; According to the example microwave network layout vector and the example microwave network layout target information corresponding to each of the example information, the candidate microwave layout analysis network is updated as follows: For each of the example information, the example microwave network layout vector corresponding to the example information is loaded into the candidate microwave layout analysis network, and the candidate microwave layout analysis network is used to analyze and generate at least one estimated microwave network layout target information corresponding to the example microwave network layout vector; According to the at least one estimated microwave network layout target information corresponding to each of the example information and the example microwave network layout target information, a network update error corresponding to the candidate microwave layout analysis network is calculated; When the network update error is less than a preset error, the current candidate microwave layout analysis network is taken as the updated microwave layout analysis network; When the network update error is greater than or equal to the preset error, the network parameters of the candidate microwave layout analysis network are updated according to the network update error, and the current updated candidate microwave layout analysis network is continuously updated according to the example microwave network layout vector and the example microwave network layout target information corresponding to each of the example information.

9. The method according to any one of claims 1 to 8, characterized in that, After the microwave network layout vector is loaded into the updated microwave layout analysis network, and the microwave layout analysis network is used to analyze and generate at least one microwave network layout target information matching the microwave network test target information, the method further comprises: When the number of the microwave network layout target information matching the microwave network test target information is equal to 1, the microwave network layout target information is taken as the final output data of the target microwave network layout task; When the number of the microwave network layout target information matching the microwave network test target information is greater than 1, the similarity between each microwave network layout target information and the current microwave network layout information is calculated respectively, and the microwave network layout target information with the maximum similarity is taken as the final output data of the target microwave network layout task.

10. A system for generating information based on microwave network testing in a super pit, characterized by Comprise: One or more processors, memories, and one or more programs, wherein the one or more programs are stored in the memories and configured to be executed by the one or more processors, and the one or more programs comprise a program for executing the method of any one of claims 1 to 9.

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