Typhoon disaster warning method, device, server and storage medium

Abstract

The present invention provides a typhoon disaster warning method, device, server and storage medium, the method comprising: obtaining the typhoon range and corresponding typhoon data provided by a typhoon data system; obtaining the alarm data of each network element in the communication system within the typhoon range; inputting the alarm data of each network element and the corresponding typhoon data into a preset decision tree warning model to determine whether each network element needs to be warned; sending the warning information of each network element that needs to be warned to a mobilization module so that the person in charge of the network element can perform maintenance to eliminate the warning fault. The typhoon disaster warning provided by the embodiment of the present invention improves the warning efficiency because it does not require manual inspection; and the warning is targeted at each network element within the typhoon range, which is targeted and improves the accuracy of the warning.

Description

Technical Field

[0001] The present invention relates to the field of communication technology, and in particular to a typhoon disaster early warning method, device, server and storage medium. Background Art

[0002] Typhoon is one of the major disastrous weather conditions that affects coastal and some inland areas. After landing, typhoon not only brings disasters such as rainstorms, strong winds and mudslides to coastal areas, but also penetrates into some inland areas to bring heavy rainfall, even causing waterlogging, resulting in huge economic losses. When a typhoon occurs, it will also cause certain damage to the communication equipment of operators. Therefore, timely warning of the impact of typhoon disasters on communication systems (composed of a large number of communication network elements) in typhoon forecasts is important for ensuring communications.

[0003] At present, the existing technology mainly performs manual inspections on key indicators of communication equipment. When the key indicators exceed a fixed threshold, an alarm is issued, and then the alarm fault is eliminated through maintenance.

[0004] However, manual inspection requires a lot of manpower and is costly. In addition, the inspection targets are unclear, making it difficult to find faulty network elements in a timely manner and making it impossible to provide accurate early warnings. Summary of the invention

[0005] The present invention provides a typhoon disaster warning method, device, server and storage medium to overcome the problem that the manual inspection method of the prior art requires a large amount of manpower for inspection, which is costly; and the inspection target is unclear, it is difficult to find the faulty network element in time, and accurate warning cannot be carried out.

[0006] In a first aspect, the present invention provides a typhoon disaster early warning method, comprising:

[0007] Obtain the typhoon range and corresponding typhoon data provided by the typhoon data system;

[0008] Acquire alarm data of each network element in the communication system within the typhoon range;

[0009] Inputting the alarm data of each network element and the corresponding typhoon data into a preset decision tree warning model to determine whether each network element needs to be warned;

[0010] The warning information of each network element that needs to be warned is sent to the dispatching module so that the person in charge of the network element can perform maintenance to eliminate the warning fault.

[0011] In one possible design, the step of establishing a preset decision tree early warning model includes: obtaining alarm data and fault data of each network element in the communication system of the target area within a preset time period, and the corresponding weather data of the target area within the preset time period; using the alarm data and typhoon data as input data sets, and the fault data as output data sets, dividing the alarm data and typhoon data according to the division rule that reduces the entropy of the data set the most, and generating the preset decision tree early warning model.

[0012] In one possible design, the obtaining of alarm data and fault data of each network element in the communication system of the target area within a preset time period, as well as the corresponding weather data of the target area within the preset time period, includes: obtaining the alarm data and fault data of each network element in the communication system of the target area, as well as the corresponding weather data of the target area within the preset time period from the network through crawler technology; storing the alarm data and fault data of each network element in the communication system of the target area within the preset time period, as well as the corresponding weather data of the target area within the preset time period in the Hadoop distributed storage system.

[0013] In one possible design, obtaining the alarm data of each network element in the communication system within the typhoon range includes: obtaining the alarm data of each network element from a base station and a network management database in the communication system within the typhoon range.

[0014] In a possible design, after the warning information of each network element that needs to be warned is sent to the mobilization module so that the person in charge of the network element can perform maintenance to eliminate the warning fault, it also includes: sending the warning information of each network element that needs to be warned to the front-end display module to display the map location information of each network element that needs to be warned.

[0015] In a second aspect, the present invention provides a typhoon disaster warning device, comprising:

[0016] A first acquisition module is used to acquire a typhoon range and corresponding typhoon data provided by a typhoon data system;

[0017] A second acquisition module is used to acquire the alarm data of each network element in the communication system within the typhoon range;

[0018] An analysis module, used for inputting the alarm data of each network element and the corresponding typhoon data into a preset decision tree warning model to determine whether each network element needs to be warned;

[0019] The early warning module is used to send the early warning information of each network element that needs early warning to the dispatching module, so that the person in charge of the network element can perform maintenance to eliminate the early warning fault.

[0020] In one possible design, the device also includes: a model building module, used to obtain alarm data and fault data of each network element in the communication system of the target area within a preset time period, and corresponding weather data of the target area within the preset time period; using the alarm data and typhoon data as input data sets, and the fault data as output data sets, dividing the alarm data and typhoon data according to the division rule that reduces the entropy of the data set the most, and generating the preset decision tree warning model.

[0021] In one possible design, the model building module is specifically used to obtain the alarm data and fault data of each network element in the communication system of the target area, as well as the corresponding weather data of the target area within a preset time period from the network through crawler technology; and store the alarm data and fault data of each network element in the communication system of the target area within the preset time period, as well as the corresponding weather data of the target area within the preset time period in the Hadoop distributed storage system.

[0022] In a third aspect, the present invention provides a server, comprising: at least one processor and a memory;

[0023] The memory stores computer-executable instructions;

[0024] The at least one processor executes the computer-executable instructions stored in the memory, so that the at least one processor executes the typhoon disaster warning method as described in the first aspect and various possible designs of the first aspect.

[0025] In a fourth aspect, the present invention provides a computer storage medium, wherein the computer storage medium stores computer execution instructions. When a processor executes the computer execution instructions, the typhoon disaster warning method described in the first aspect and various possible designs of the first aspect is implemented.

[0026] The typhoon disaster warning method, device, server and storage medium provided by the present invention improve the warning efficiency because no manual inspection is required; and the warning is carried out for each network element within the typhoon range, which is targeted and improves the accuracy of the warning. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative labor.

[0028] Figure 1 is a schematic diagram of the architecture of a typhoon disaster warning system provided by an embodiment of the present invention;

[0029] Figure 2 Schematic diagram of the typhoon disaster warning method provided by the embodiment of the present invention Figure 1 ;

[0030] Figure 3 Schematic diagram of the typhoon disaster warning method provided by the embodiment of the present invention Figure 2 ;

[0031] Figure 4 The structural frame of the typhoon disaster warning device provided in the embodiment of the present disclosure is Figure 1 ;

[0032] Figure 5 The structural frame of the typhoon disaster warning device provided in the embodiment of the present disclosure is Figure 2 ;

[0033] Figure 6 A schematic diagram of the hardware structure of a server provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0034] In order to make the purpose, technical solution and advantages of the embodiments of the present invention clearer, the technical solution in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0035] Typhoon disasters occur suddenly, and the impact on the communication system is not easy to discover in advance. Since the traditional manual inspection guarantee scheme cannot effectively and accurately warn the situation of communication equipment, the present invention provides a disaster warning method. First, a decision tree warning model is established based on big data, and then the typhoon data predicted by the typhoon system and the alarm data of each network element within the corresponding typhoon range are obtained. The typhoon data and the alarm data of each network element are input into the decision tree warning model to determine the network elements that need to be warned. Finally, the warning information of each network element that needs to be warned is sent to the person in charge of the network element for maintenance and elimination of the warning fault. Since manual inspection is not required, the warning efficiency is improved, and the warning is targeted at each network element within the typhoon range, which is targeted and improves the accuracy of the warning.

[0036] Figure 1 Schematic diagram of the architecture of the typhoon disaster warning system provided by the embodiment of the present invention. Figure 1 As shown, the typhoon disaster warning system includes: a processing module 101, a mobilization module 102 and a front-end display module 103, etc.

[0037] The processing module 101 may be a server or a cluster consisting of several servers.

[0038] The mobilization module 102 may be a terminal device, for example, any form of terminal device. The terminal device involved in the present disclosure may be a wireless terminal or a wired terminal. A wireless terminal may be a device that provides voice and / or other service data connectivity to a user, a handheld device with a wireless connection function, or other processing devices connected to a wireless modem. A wireless terminal may communicate with one or more core network devices via a radio access network (Radio Access Network, referred to as RAN). A wireless terminal may be a mobile terminal, such as a mobile phone (or "cellular" phone) and a computer with a mobile terminal, for example, a portable, pocket-sized, handheld, computer-built-in or vehicle-mounted mobile device, which exchanges language and / or data with a radio access network. For another example, a wireless terminal may also be a personal communication service (PCS) phone, a cordless phone, a session initiation protocol (SIP) phone, a wireless local loop (WLL) station, a personal digital assistant (PDA) and the like. The wireless terminal may also be referred to as a system, a subscriber unit, a subscriber station, a mobile station, a mobile station, a remote station, a remote terminal, an access terminal, a user terminal, a user agent, or a user device or user equipment, without limitation. Optionally, the terminal device may also be a mobile phone, a smart wearable device, a tablet computer, or other terminal device.

[0039] The front-end display module 103 may be a large-size display device, such as a television or a projector.

[0040] Figure 2 Schematic diagram of the typhoon disaster warning method provided by the embodiment of the present invention Figure 1 The execution subject of this embodiment can be Figure 1 The processing module 101 in the illustrated embodiment. Figure 2 As shown, the method includes:

[0041] S201: Obtain the typhoon range and corresponding typhoon data provided by the typhoon data system.

[0042] In this embodiment, the typhoon data system may be an official website such as China Weather Network. The typhoon range and corresponding typhoon data provided by the typhoon data system are all the predicted typhoon range and corresponding typhoon data.

[0043] The typhoon range may be obtained based on an electronic map.

[0044] Typhoon data refers to the real-time typhoon data provided by the meteorological department's observation station, including the latitude and longitude coordinates of the typhoon center, the central wind force, the measured radius of the level 7 wind circle, and the measured radius of the level 10 wind circle, and the typhoon data is updated in real time.

[0045] S202: Acquire alarm data of each network element in the communication system within the typhoon range.

[0046] Specifically, the alarm data of each network element is obtained from each base station and network management database in the communication system within the typhoon range.

[0047] In this embodiment, the communication system within the typhoon path is determined according to the typhoon path in the typhoon range, and the alarm data of each network element of the communication system is obtained through real-time network communication. The network elements in the communication system include but are not limited to optical cables, relay stations, office buildings, base stations, etc.

[0048] S203: Input the alarm data of each network element and the corresponding typhoon data into a preset decision tree warning model to determine whether each network element needs to be warned.

[0049] In this embodiment, the alarm data and corresponding typhoon data of each network element are input into a preset decision tree warning model. Based on the judgment of the alarm data and typhoon data with the preset thresholds, it is finally determined whether each network element is a network element that requires warning.

[0050] Among them, the typhoon data includes the typhoon level and the distance from the network element; the alarm data is the number of alarms of the network element.

[0051] S204: Send the warning information of each network element that needs warning to the dispatching module, so that the person in charge of the network element can perform maintenance to eliminate the warning fault.

[0052] In this embodiment, the warning information of each network element that needs to be warned is pushed to the terminal device of the person in charge of the network element through the instant messaging software.

[0053] From the above description, it can be seen that the typhoon disaster warning provided by the embodiment of the present invention improves the warning efficiency because it does not require manual inspection; and the warning is carried out for each network element within the typhoon range, which is targeted and improves the accuracy of the warning.

[0054] Figure 3Schematic diagram of the typhoon disaster warning method provided by the embodiment of the present invention Figure 2 In the embodiment of the present invention, Figure 2 Based on the embodiments provided above, this embodiment mainly describes the process of establishing a preset decision tree early warning model. Figure 3 As shown, the method includes:

[0055] S301: Acquire alarm data and fault data of each network element in a communication system of a target area within a preset time period, and corresponding typhoon data of the target area within the preset time period.

[0056] In this embodiment, the preset time period may be 1 year or 5 years, and the present invention does not impose any limitation on this. The fault data includes statistical data of whether each network element in the communication system has a fault or not.

[0057] Specifically, the alarm data and fault data of each network element in the communication system of the target area and the corresponding weather data of the target area within a preset time period are obtained from the network through crawler technology; the alarm data and fault data of each network element in the communication system of the target area within the preset time period and the corresponding weather data of the target area within the preset time period are stored in the Hadoop distributed storage system.

[0058] Among them, the Hadoop distributed storage system has high reliability: data storage, multiple copies of data blocks; data calculation, rescheduling of job calculations, and automatic scheduling and calculation if an exception occurs. The Hadoop distributed storage system has high scalability: when storage and computing resources are insufficient, it can be expanded horizontally linearly; a cluster can include thousands of nodes. The Hadoop distributed storage system has the characteristics of low cost: storage on ordinary cheap machines, with a mature ecosystem.

[0059] In this embodiment, according to different data types and granularities, the kafka interface is used to collect real-time data, and the ftp interface is used to collect file data.

[0060] S302: Use the alarm data and typhoon data as input data sets and the fault data as output data sets, divide the alarm data and typhoon data according to the division rule that reduces the entropy of the data sets the most, and generate the preset decision tree warning model.

[0061] Specifically, the alarm data and typhoon data are divided according to the division rule that reduces the entropy of the data set the most, and the input data set is divided into several sub-data sets. Then, the alarm data and typhoon data are further divided according to the division rule that reduces the entropy of the data set the most, until all the input data sets of the alarm data and typhoon data are divided or the remaining sub-data sets belong to the classification result of the same fault data.

[0062] In this embodiment, the decision tree is a machine learning classification algorithm; the alarm data and typhoon data are used as input data sets to represent attributes; the fault data is used as the output data set to represent the classification result.

[0063] From the above description, it can be seen that the decision tree warning model established through big data can provide typhoon disaster warning for the communication system more accurately.

[0064] In one embodiment of the present invention, based on the above embodiment, after step S204: sending the warning information of each network element that needs to be warned to the mobilization module so that the person in charge of the network element can perform maintenance to eliminate the warning fault, the following may also be included:

[0065] The warning information of each network element that needs to be warned is sent to the front-end display module to display the map location information of each network element that needs to be warned.

[0066] The warning information of each network element may be the location information of each warning network element in the electronic map.

[0067] In this embodiment, the information that can also be displayed on the front-end display module includes but is not limited to: emergency command information, real-time typhoon route, and on-duty information of each network element.

[0068] Corresponding to the typhoon disaster early warning method in the above embodiment, Figure 4 The structural frame of the typhoon disaster warning device provided in the embodiment of the present disclosure is Figure 1 For ease of explanation, only the parts related to the embodiments of the present disclosure are shown. Figure 4 As shown, the typhoon disaster warning device includes: a first acquisition module 401, a second acquisition module 402, an analysis module 403 and a warning module 404.

[0069] Among them, the first acquisition module 401 is used to obtain the typhoon range and corresponding typhoon data provided by the typhoon data system; the second acquisition module 402 is used to obtain the alarm data of each network element in the communication system within the typhoon range; the analysis module 403 is used to input the alarm data of each network element and the corresponding typhoon data into a preset decision tree early warning model to determine whether each network element needs to be warned; the early warning module 404 is used to send the early warning information of each network element that needs to be warned to the mobilization module, so that the person in charge of the network element can perform maintenance to eliminate the early warning fault.

[0070] From the above description, it can be seen that the typhoon disaster warning provided by the embodiment of the present invention improves the warning efficiency because it does not require manual inspection; and the warning is carried out for each network element within the typhoon range, which is targeted and improves the accuracy of the warning.

[0071] refer to Figure 5 In a possible implementation, the typhoon disaster warning device also includes: a model building module 405, which is used to obtain the alarm data and fault data of each network element in the communication system of the target area within a preset time period, and the corresponding weather data of the target area within the preset time period; using the alarm data and typhoon data as input data sets, and the fault data as output data sets, and dividing the alarm data and typhoon data according to the division rule that reduces the entropy of the data set the most, to generate the preset decision tree warning model.

[0072] In one possible implementation, the model building module 405 is specifically used to obtain the alarm data and fault data of each network element in the communication system of the target area, as well as the corresponding weather data of the target area within a preset time period from the network through crawler technology; and store the alarm data and fault data of each network element in the communication system of the target area within the preset time period, as well as the corresponding weather data of the target area within the preset time period in the Hadoop distributed storage system.

[0073] In a possible implementation, the second acquisition module 402 is specifically configured to acquire the alarm data of each network element from each base station and a network management database in the communication system within the typhoon range.

[0074] refer to Figure 5 In a possible implementation, the typhoon disaster warning device also includes: a display module 406, which is used to send the warning information of each network element that needs to be warned to the mobilization module so that the person in charge of the network element can perform maintenance to eliminate the warning fault, and then send the warning information of each network element that needs to be warned to the front-end display module to display the map location information of each network element that needs to be warned.

[0075] The device provided in this embodiment can be used to execute the technical solution of the above method embodiment. Its implementation principle and technical effect are similar, and this embodiment will not be repeated here.

[0076] Figure 6 The hardware structure diagram of the server provided in the embodiment of the present invention is shown in FIG. Figure 6 As shown, the server 60 of this embodiment includes: a processor 601 and a memory 602;

[0077] Memory 602, used to store computer-executable instructions;

[0078] The processor 601 is used to execute the computer-executable instructions stored in the memory to implement the various steps executed by the server in the above embodiment. For details, please refer to the relevant description in the above method embodiment.

[0079] Optionally, the memory 602 may be independent or integrated with the processor 601 .

[0080] When the memory 602 is independently provided, the server further includes a bus 603 for connecting the memory 602 and the processor 601 .

[0081] An embodiment of the present invention further provides a computer storage medium, in which computer execution instructions are stored. When a processor executes the computer execution instructions, the typhoon disaster warning method as described above is implemented.

[0082] The embodiment of the present invention further provides a computer program product, including a computer program, which, when executed by a processor, implements the typhoon disaster warning method as described above. The embodiment of the present invention further provides a computer program product, including a computer program, which, when executed by a processor, implements the typhoon disaster warning method as described above.

[0083] In the several embodiments provided by the present invention, it should be understood that the disclosed devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic, for example, the division of the modules is only a logical function division, and there may be other division methods in actual implementation, such as multiple modules can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be an indirect coupling or communication connection through some interfaces, devices or modules, which can be electrical, mechanical or other forms.

[0084] The modules described as separate components may or may not be physically separated, and the components shown as modules may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the modules may be selected according to actual needs to implement the solution of this embodiment.

[0085] In addition, each functional module in each embodiment of the present invention may be integrated into one processing unit, or each module may exist physically separately, or two or more modules may be integrated into one unit. The above-mentioned module-composed unit may be implemented in the form of hardware or in the form of hardware plus software functional units.

[0086] The above-mentioned integrated module implemented in the form of a software function module can be stored in a computer-readable storage medium. The above-mentioned software function module is stored in a storage medium, including a number of instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) or a processor to perform some steps of the method described in each embodiment of the present application.

[0087] It should be understood that the processor may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), etc. A general-purpose processor may be a microprocessor or any conventional processor. The steps of the method disclosed in the invention may be directly implemented as being executed by a hardware processor, or may be implemented by a combination of hardware and software modules in the processor.

[0088] The memory may include a high-speed RAM memory, and may also include a non-volatile storage NVM, such as at least one disk memory, and may also be a USB flash drive, a mobile hard disk, a read-only memory, a magnetic disk or an optical disk, etc.

[0089] The bus may be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, or an Extended Industry Standard Architecture (EISA) bus, etc. The bus may be divided into an address bus, a data bus, a control bus, etc. For ease of representation, the bus in the drawings of the present application is not limited to only one bus or one type of bus.

[0090] The above storage medium can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic disk or optical disk. The storage medium can be any available medium that can be accessed by a general or special purpose computer.

[0091] An exemplary storage medium is coupled to a processor so that the processor can read information from the storage medium and write information to the storage medium. Of course, the storage medium can also be a component of the processor. The processor and the storage medium can be located in an application specific integrated circuit (ASIC). Of course, the processor and the storage medium can also exist as discrete components in an electronic device or a main control device.

[0092] Those skilled in the art can understand that all or part of the steps of implementing the above-mentioned method embodiments can be completed by hardware related to program instructions. The aforementioned program can be stored in a computer-readable storage medium. When the program is executed, the steps of the above-mentioned method embodiments are executed; and the aforementioned storage medium includes: ROM, RAM, disk or optical disk and other media that can store program codes.

[0093] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or replace some or all of the technical features therein with equivalents. However, these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. A typhoon disaster early warning method, characterized in that: include: Obtain the typhoon range and corresponding typhoon data provided by the typhoon data system; Acquire alarm data of each network element in the communication system within the typhoon range; The alarm data includes: the number of alarms of the network element; Inputting the alarm data of each network element and the corresponding typhoon data into a preset decision tree warning model to determine whether each network element needs to be warned; Send the warning information of each network element that needs warning to the dispatch module, so that the person in charge of the network element can perform maintenance to eliminate the warning fault; The step of establishing the preset decision tree early warning model includes: Acquire alarm data and fault data of each network element in the communication system of the target area within a preset time period, as well as corresponding weather data of the target area within the preset time period; Using the alarm data and typhoon data as input data sets and the fault data as output data sets, dividing the alarm data and typhoon data according to the division rule that reduces the entropy of the data sets the most, and generating the preset decision tree warning model; The method of dividing the warning data and the typhoon data according to the division rule that reduces the entropy of the data set the most, and generating the preset decision tree warning model, includes: The alarm data and typhoon data are divided according to the division rule with the largest entropy reduction of the data set to divide the input data set into several sub-data sets, and the alarm data and typhoon data are continued to be divided according to the division rule with the largest entropy reduction of the data set until all the input data sets of the alarm data and typhoon data are divided or the remaining sub-data sets belong to the classification result of the same fault data.

2. The method according to claim 1, characterized in that The obtaining of alarm data and fault data of each network element in the communication system of the target area within the preset time period, and corresponding weather data of the target area within the preset time period, includes: Acquire alarm data and fault data of each network element in the communication system of the target area from the network through crawler technology, as well as the corresponding weather data of the target area within a preset time period; The alarm data and fault data of each network element in the communication system of the target area within the preset time period and the corresponding weather data of the target area within the preset time period are stored in the Hadoop distributed storage system.

3. The method according to claim 1, characterized in that The obtaining of alarm data of each network element in the communication system within the typhoon range includes: Obtain the alarm data of each network element from the base stations and network management database in the communication system within the typhoon range.

4. The method according to any one of claims 1 to 3, characterized in that: After sending the warning information of each network element that needs warning to the dispatching module so that the person in charge of the network element can perform maintenance to eliminate the warning fault, it also includes: The warning information of each network element that needs to be warned is sent to the front-end display module to display the map location information of each network element that needs to be warned.

5. A typhoon disaster warning device, characterized in that: include: A first acquisition module is used to acquire a typhoon range and corresponding typhoon data provided by a typhoon data system; The second acquisition module is used to acquire the alarm data of each network element in the communication system within the typhoon range; the alarm data includes: the number of alarms of the network element; An analysis module, used for inputting the alarm data of each network element and the corresponding typhoon data into a preset decision tree warning model to determine whether each network element needs to be warned; The early warning module is used to send the early warning information of each network element that needs early warning to the dispatch module, so that the person in charge of the network element can perform maintenance to eliminate the early warning fault; The typhoon disaster warning device also includes: a model building module, which is used to obtain the alarm data and fault data of each network element in the communication system of the target area within a preset time period, and the corresponding weather data of the target area within the preset time period; using the alarm data and typhoon data as input data sets, and the fault data as output data sets, and dividing the alarm data and typhoon data according to the division rule that reduces the entropy of the data set the most, to generate the preset decision tree warning model; The model building module is also used for: The alarm data and typhoon data are divided according to the division rule with the largest entropy reduction of the data set to divide the input data set into several sub-data sets, and the alarm data and typhoon data are continued to be divided according to the division rule with the largest entropy reduction of the data set until all the input data sets of the alarm data and typhoon data are divided or the remaining sub-data sets belong to the classification result of the same fault data.

6. The device according to claim 5, characterized in that The model building module is specifically used to obtain the alarm data and fault data of each network element in the communication system of the target area from the network through the crawler technology, as well as the corresponding weather data of the target area within a preset time period; The alarm data and fault data of each network element in the communication system of the target area within the preset time period and the corresponding weather data of the target area within the preset time period are stored in the Hadoop distributed storage system.

7. A server, characterized in that: include: at least one processor and memory; The memory stores computer-executable instructions; The at least one processor executes the computer-executable instructions stored in the memory, so that the at least one processor executes the typhoon disaster warning method according to any one of claims 1 to 4.

8. A computer storage medium, characterized in that: The computer storage medium stores computer execution instructions, and when the processor executes the computer execution instructions, the typhoon disaster warning method according to any one of claims 1 to 4 is implemented.

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