Operation strategy generation method and device, equipment and storage medium

Abstract

The invention discloses an operation strategy generation method and device, equipment and a storage medium, and belongs to the technical field of spatial analysis. The method comprises the following steps: acquiring spatial business data, and generating a business data layer according to the spatial business data; layering the business data layer to obtain a plurality of layer structures; performing slicing and coordinate conversion on the layer structure to obtain conversion coordinate information; and obtaining government and enterprise distribution information according to the conversion coordinate information and a preset spatial analysis model, and generating a market operation strategy according to the government and enterprise distribution information. In this way, the space resource calculation process is calculated through the rear-end server, the calculation efficiency is greatly improved, finally, the space resources are displayed at the WEB end in a compressed picture mode, excessive WEB end resources do not need to be occupied, only loading display needs to be carried out, the system loading efficiency and user perception are effectively improved, and the user experience is improved. And the finally auxiliary generated market operation strategy is more visual and convenient.

Description

Technical Field

[0001] The present invention relates to the field of spatial analysis technology, and in particular to an operation strategy generation method, device, equipment and storage medium. Background Art

[0002] As GIS map technology matures, the market has launched open GIS map APIs for developers, including basic map functions, such as panning, zooming, dragging, etc., as well as controls on the map. If we open the map now, we can see functions such as positioning and zooming on the map, as well as tools, layers, local search, bus chains, walking navigation, etc. These make it convenient for users to call map-related functions with a low access threshold.

[0003] The existing commonly used layer display uses the map display function, which lacks spatial analysis capabilities and display efficiency. When rendering the map, marking points, lines, and surface objects requires a large amount of WEB computing resources and computing power. Due to the low capacity of available computing resources on the WEB, when performing map rendering and spatial analysis with large amounts of data, it will lead to performance efficiency issues such as slow WEB page display efficiency and page freezes.

[0004] The above contents are only used to assist in understanding the technical solution of the present invention and do not constitute an admission that the above contents are prior art. Summary of the invention

[0005] The main purpose of the present invention is to provide an operation strategy generation method, device, equipment and storage medium, aiming to solve the technical problem that the prior art requires a large amount of web-side computing resources when rendering maps, resulting in low web-side page display efficiency, page freezes, and inconvenience in combining maps and data for analysis.

[0006] To achieve the above object, the present invention provides an operation strategy generation method, which comprises the following steps: Acquire spatial business data, and generate a business data layer according to the spatial business data; Layering the business data layer to obtain multiple layer structures; Slicing and coordinate conversion of the layer structure to obtain conversion coordinate information; The government-enterprise distribution information is obtained according to the converted coordinate information and a preset spatial analysis model, and a market operation strategy is generated according to the government-enterprise distribution information.

[0007] Optionally, slicing and coordinate transforming the layer structure to obtain transformed coordinate information includes: Determine the thematic layer according to the layer structure; Slicing the thematic layer to obtain a layer slicing result; The layer slicing result is subjected to coordinate transformation to obtain transformation coordinate information.

[0008] Optionally, after performing coordinate transformation on the layer slicing result to obtain transformation coordinate information, the method further includes: Performing basic coordinate correction on the layer slicing result to obtain basic correction information; Calculate correction parameters according to the basic correction information; A correction algorithm is obtained according to the correction parameters, and the conversion coordinate information is optimized according to the correction algorithm.

[0009] Optionally, performing coordinate transformation on the layer slicing result to obtain transformation coordinate information includes: Get the preset coordinate calculation formula and projection reverse calculation formula; The layer slicing result is subjected to coordinate transformation based on the geodetic coordinate system by using the preset coordinate calculation formula and the projection reverse calculation formula to obtain transformation coordinate information.

[0010] Optionally, obtaining government-enterprise distribution information according to the converted coordinate information and a preset spatial analysis model includes: Determine position grid information according to the converted coordinate information; Calculate the government-enterprise aggregation degree according to the location grid information and the spatial business data; The government-enterprise distribution information is determined according to the government-enterprise concentration degree.

[0011] Optionally, the calculating the government-enterprise aggregation degree according to the location grid information and the spatial business data includes: Determine the distribution location of government and enterprise users in each grid according to the location grid information; Calculate the proximity of government and enterprise users according to the distribution locations of the government and enterprise users and the spatial service data; The government-enterprise aggregation degree is obtained according to the government-enterprise user proximity degree.

[0012] Optionally, generating a market operation strategy according to the government-enterprise distribution information includes: Determine a key grid according to the government and enterprise distribution information and the location grid information; Predicting a grid service type according to the key grid and the service attribute information; A market operation strategy is generated according to the grid service type.

[0013] In addition, to achieve the above-mentioned purpose, the present invention further proposes an operation strategy generating device, the operation strategy generating device comprising: A layer generation module, used to obtain spatial service data and generate a service data layer according to the spatial service data; A layer layering module, used for layering the business data layer to obtain multiple layer structures; A coordinate conversion module, used for slicing and coordinate conversion of the layer structure to obtain conversion coordinate information; A strategy generation module is used to obtain government-enterprise distribution information based on the converted coordinate information and a preset spatial analysis model, and to generate a market operation strategy based on the government-enterprise distribution information.

[0014] In addition, to achieve the above-mentioned purpose, the present invention also proposes an operation strategy generation device, which includes: a memory, a processor, and an operation strategy generation program stored in the memory and running on the processor, and the operation strategy generation program is configured to implement the operation strategy generation method described above.

[0015] In addition, to achieve the above-mentioned purpose, the present invention further proposes a storage medium, on which an operation strategy generation program is stored, and when the operation strategy generation program is executed by a processor, the operation strategy generation method as described above is implemented.

[0016] The present invention obtains spatial business data, and generates a business data layer according to the spatial business data; the business data layer is layered to obtain multiple layer structures; the layer structure is sliced ​​and coordinate converted to obtain conversion coordinate information; government and enterprise distribution information is obtained according to the conversion coordinate information and a preset spatial analysis model, and a market operation strategy is generated according to the government and enterprise distribution information. In this way, the generation, layering and slicing of layers based on spatial business data are realized, and then coordinate conversion is performed. Since the process of spatial resource calculation is calculated by the back-end server, the calculation efficiency is greatly improved, and it is finally displayed on the WEB side in the form of compressed images, which does not need to occupy too many WEB resources, and only needs to be loaded and displayed, which effectively improves the system loading efficiency and user perception, and the market operation strategy finally assisted in being generated is more intuitive and convenient. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Figure 1 It is a structural diagram of an operation strategy generating device of a hardware operating environment involved in an embodiment of the present invention; Figure 2 This is a flow chart of the first embodiment of the method for generating an operation strategy of the present invention; Figure 3 This is a schematic diagram of the layer structure function in an embodiment of the operation strategy generation method of the present invention; Figure 4 A schematic diagram of distribution locations in an embodiment of an operation strategy generation method of the present invention; Figure 5 A schematic diagram of the government-enterprise aggregation in an embodiment of the operation strategy generation method of the present invention; Figure 6 A schematic diagram of a flow chart of a second embodiment of the method for generating an operation strategy of the present invention; Figure 7 This is a structural block diagram of the first embodiment of the operation strategy generating device of the present invention.

[0018] The realization of the purpose, functional features and advantages of the present invention will be further explained in conjunction with embodiments and with reference to the accompanying drawings. DETAILED DESCRIPTION

[0019] It should be understood that the specific embodiments described herein are only used to explain the present invention, and are not used to limit the present invention.

[0020] Reference Figure 1 , Figure 1 A schematic diagram of a device structure is generated for an operation strategy of a hardware operating environment involved in an embodiment of the present invention.

[0021] like Figure 1 As shown, the operation strategy generation device may include: a processor 1001, such as a central processing unit (CPU), a communication bus 1002, a user interface 1003, a network interface 1004, and a memory 1005. Among them, the communication bus 1002 is used to realize the connection and communication between these components. The user interface 1003 may include a display screen (Display), an input unit such as a keyboard (Keyboard), and the optional user interface 1003 may also include a standard wired interface and a wireless interface. The network interface 1004 may optionally include a standard wired interface and a wireless interface (such as a wireless fidelity (Wireless-Fidelity, Wi-Fi) interface). The memory 1005 may be a high-speed random access memory (Random Access Memory, RAM) memory, or a stable non-volatile memory (Non-Volatile Memory, NVM), such as a disk memory. The memory 1005 may also be a storage device independent of the aforementioned processor 1001.

[0022] Those skilled in the art will understand that Figure 1 The structure shown in the figure does not constitute a limitation on the operation strategy generating device, and may include more or less components than those shown in the figure, or combine certain components, or arrange the components differently.

[0023] like Figure 1As shown, the memory 1005 as a storage medium may include an operating system, a network communication module, a user interface module, and an operation strategy generation program.

[0024] exist Figure 1 In the operation strategy generation device shown, the network interface 1004 is mainly used for data communication with the network server; the user interface 1003 is mainly used for data interaction with the user; the processor 1001 and the memory 1005 in the XX device of the present invention can be set in the operation strategy generation device, and the operation strategy generation device calls the operation strategy generation program stored in the memory 1005 through the processor 1001, and executes the operation strategy generation method provided by the embodiment of the present invention.

[0025] The embodiment of the present invention provides a method for generating an operation strategy, referring to Figure 2 , Figure 2 The figure is a flow chart of a first embodiment of a method for generating an operation strategy according to the present invention.

[0026] In this embodiment, the operation strategy generation method includes the following steps: Step S10: Acquire spatial business data, and generate a business data layer according to the spatial business data.

[0027] In this embodiment, the execution subject of this embodiment can be the operation strategy generation device, which has functions such as data processing, data communication and program running, and the operation strategy generation device can be an intelligent terminal or a server. Of course, it can also be other devices with similar functions, and this implementation condition does not limit this. For the convenience of explanation, this implementation mode takes the operation strategy generation device as an example for explanation.

[0028] It should be noted that with the maturity of GIS map technology, the market has launched open GIS map APIs for developers, including basic map functions, including panning, zooming, dragging, etc., as well as controls on the map. If we open the map now, we can see functions such as positioning and zooming on the map, as well as tools, layers, local search, bus chains, walking navigation, etc. These are convenient for users to call map-related functions with a low access threshold. At present, ArcGIS has relatively complete functions in basic map display, and its functional technologies in layer management and spatial analysis are also relatively mature. Although ArcGIS has a wide range of applications at home and abroad, due to its commercial software attributes, the underlying core code is not transparent, there are high risks of data leakage and data security, and it does not meet the requirements of the data security standards related to the information innovation in the subsequent market development. The existing common technical solutions are based on the traditional GIS engine application layer management function, which realizes the graphical loading and display of various layers. Its main functions are WMS service publishing, layer cutting display, spatial analysis and other geographic information system technologies. The existing commonly used layer display uses the map display function, which lacks spatial analysis capabilities and display efficiency. When rendering a map, it is necessary to mark points, lines, and surface objects, which consumes a large amount of WEB computing resources and computing power. Due to the low capacity of available computing resources on the WEB side, when performing map rendering and spatial analysis with a large amount of data, it will cause performance efficiency problems such as low WEB page display efficiency and page jams. Although the current ArcGIS engine is comprehensive and powerful, it has data leakage and information security risks. At the same time, some open source GIS engines have problems such as imperfect functions and low data processing performance. The solution of this embodiment realizes the layer management function of the geographic information system engine through a self-built algorithm, realizes the layer calculation of spatial data, and realizes the cutting, compression, and layer display of spatial shape files. Since the process of spatial resource calculation is calculated by the back-end server, the calculation efficiency is greatly improved, and finally displayed on the WEB side in the form of compressed pictures, it does not need to occupy too many WEB resources, and only needs to be loaded and displayed, which effectively improves the system loading efficiency and user perception.

[0029] It should be understood that spatial business data refers to data obtained based on the spatial data of business elements such as mobile channels, base stations, cells, grids, government and enterprise customers; first, spatial business data management is carried out, and first, the spatial data of business elements such as mobile channels, base stations, cells, grids, government and enterprise customers are sorted according to the open spatial data management format shapefile to obtain spatial business data.

[0030] In the specific implementation, the business data layer refers to: organizing the spatial data of business elements such as mobile channels, base stations, communities, grids, government and enterprise customers according to the open spatial data management format shapefile, generating relevant business data layers, and creating a spatial database to store and load spatial layer data in the spatial database, and loading the shapefile server through algorithms.

[0031] Step S20: layering the business data layer to obtain multiple layer structures.

[0032] It should be noted that the business data layer adopts a three-layer spatial data structure, namely, terrain layer, thematic layer, and marker layer. Among them, the thematic layer mainly includes spatial business data information such as base stations, channels, communities, government and enterprise units.

[0033] It should be understood that in the self-developed map engine, a three-layer spatial data structure is used for the map, namely the terrain layer, the thematic layer, and the marker layer. The terrain layer is the most basic topographic map and image map slice, which contains terrain information such as streets, buildings, lakes, mountains, and rivers. The terrain layer is also a necessary bottom layer for all GIS systems. The thematic layer is the core part of the self-developed map engine. The thematic layer mainly includes spatial business data information such as base stations, channels, communities, government and enterprise units in business applications. Usually, the data volume of this part of the data is large and the distribution is also relatively concentrated. The marker layer is at the top level of the map. The role of this layer is to realize the personalized layer of business element marking, including the web-side loading elements with a small number of temporarily marked points, lines, and surfaces on the map, such as channel marking, scene collection of target points, and other marking functions. The functions of the three layer structures are as follows: Figure 3 shown.

[0034] Step S30: Slicing and coordinate conversion are performed on the layer structure to obtain conversion coordinate information.

[0035] In a specific implementation, the thematic layer is firstly extracted from the layer structure, then the thematic layer is sliced, and finally the coordinate transformation is performed on the layer slicing result, so as to obtain the transformation coordinate information.

[0036] Step S40: Obtaining government-enterprise distribution information according to the converted coordinate information and a preset spatial analysis model, and generating a market operation strategy according to the government-enterprise distribution information.

[0037] It should be noted that the grid information of each location and the government and enterprise location information within the grid are first determined based on the converted coordinate information, and then the location grid information is combined with the spatial business data to calculate the government and enterprise aggregation degree, and finally the government and enterprise distribution information is determined based on the government and enterprise aggregation degree.

[0038] Furthermore, in order to accurately determine the government and enterprise distribution information, the step S40 of obtaining the government and enterprise distribution information based on the converted coordinate information and the preset spatial analysis model includes: determining the location grid information based on the converted coordinate information; calculating the government and enterprise clustering degree based on the location grid information and the spatial business data; and determining the government and enterprise distribution information based on the government and enterprise clustering degree.

[0039] It should be understood that by adding a spatial analysis model to the self-developed layer management algorithm, the spatial information elements in the geographic information system, such as length, area, proximity, spatial distribution and other spatial attributes, are incorporated into the traditional system statistical analysis, and then the data transaction phenomena related to spatial location are studied, the spatial distribution relationship is explored, and the spatial distribution laws of business elements are found, which provides data basis for market management and development, thereby improving management and operating efficiency.

[0040] In the specific implementation, in spatial analysis, for government and enterprise business, the spatial adjacent distribution algorithm of self-developed spatial analysis is used to count the spatial concentration and dispersion attributes of different enterprises. The application scenario is to analyze the distribution of different types of government and enterprise customers in a fixed analysis area, such as cities, business departments, grids and other management unit areas; or to analyze the same type of government and enterprise customers in a fixed management area, with different time dimensions such as years and months.

[0041] It should be noted that, first of all, the government and enterprise customers are classified according to the major categories, totaling 21 categories: mining, production and supply of electricity, gas and water, real estate, public administration and social organizations, national defense, international organizations, construction, transportation, warehousing and postal services, education, finance, resident services and other services, scientific research, technical services and geological exploration, agriculture, forestry, animal husbandry, fishery, wholesale and retail, water conservancy, environment and public facilities management, health, social security and social welfare, culture, sports and entertainment, information transmission, computer services and software, manufacturing, accommodation and catering, leasing and business services, and the data is classified and calculated according to the management grid, and the distribution details of government and enterprise customers of each category in all grids are calculated to obtain the location grid information. Then, the spatial adjacent algorithm is used to calculate the aggregation degree of government and enterprise customers in different grids in combination with spatial business data, and finally the government and enterprise distribution information is determined according to the aggregation degree.

[0042] In this way, it is possible to determine the distribution information of government and enterprises through grid computing.

[0043] Furthermore, in order to accurately calculate the government-enterprise aggregation degree, the step of calculating the government-enterprise aggregation degree based on the location grid information and the spatial business data includes: determining the distribution position of government and enterprise users in each grid based on the location grid information; calculating the government and enterprise user proximity based on the government and enterprise user distribution position and the spatial business data; and obtaining the government and enterprise aggregation degree based on the government and enterprise user proximity.

[0044] It should be understood that the distribution locations of government and enterprise users in each grid are first determined based on the location grid information, and then the proximity of government and enterprise users is calculated in combination with the spatial service data. The specific calculation method is: Where d is the distance between each government and enterprise user, d k The value of is determined by the distribution location of government and enterprise users. Figure 4 shown.

[0045] In the specific implementation, D0 is used to judge the degree of dispersion and aggregation of the distribution of the research object. The degree of aggregation is from low to high, from dispersion to aggregation, such as Figure 5 shown.

[0046] In this way, accurate calculation of government-enterprise concentration is achieved, thereby generating market operation strategies more accurately.

[0047] Furthermore, in order to accurately generate market operation strategies, generating market operation strategies based on the government-enterprise distribution information in step S40 includes: determining key grids based on the government-enterprise distribution information and the location grid information; predicting grid business types based on the key grids and the business attribute information; and generating market operation strategies based on the grid business types.

[0048] It should be noted that, finally, the k-means clustering algorithm is used to combine the distribution of government and enterprise customers in the above grids and the results obtained by the spatial adjacent algorithm to comprehensively calculate the key grids. This detailed result is used as the basis for model training. The grid business type is regularly predicted based on the group attributes every month, and users conduct key grid marketing based on local conditions. Analyze the concentrated and dispersed attributes of the distribution of elements of cities, business departments, and grids in different management areas to formulate targeted operation strategies to achieve effective operations and thus improve market operation efficiency.

[0049] It should be understood that the algorithm of this embodiment integrates the statistical attribute data and spatial location data of the research object, and analyzes the distribution of different types of government and enterprise customers or research objects in a fixed analysis area, such as a prefecture-level city, business department, grid and other management unit areas; or analyzes the same type of government and enterprise customers in a fixed management area, with different time dimensions such as years and months. The algorithm can provide personalized and targeted operational support for business support systems managed in a grid manner, thereby improving operational efficiency.

[0050] In this way, accurate marketing strategies can be generated based on grid information and the distribution location, concentration, and other information of government and enterprise customers, thereby improving the efficiency of market operations.

[0051] This embodiment obtains spatial business data, and generates a business data layer based on the spatial business data; layers the business data layer to obtain multiple layer structures; slices and coordinates the layer structure to obtain conversion coordinate information; obtains government and enterprise distribution information based on the conversion coordinate information and a preset spatial analysis model, and generates a market operation strategy based on the government and enterprise distribution information. In this way, the generation, layering and slicing of layers based on spatial business data are realized, and then coordinate conversion is performed. Since the spatial resource calculation process is calculated through the back-end server, the calculation efficiency is greatly improved, and it is finally displayed on the WEB side in the form of compressed images, which does not need to occupy too many WEB resources, and only needs to be loaded and displayed, which effectively improves the system loading efficiency and user perception, and the market operation strategy finally assisted in being generated is more intuitive and convenient.

[0052] refer to Figure 6 , Figure 6 This is a flow chart of a second embodiment of a method for generating an operation strategy according to the present invention.

[0053] Based on the first embodiment described above, the operation strategy generation method of this embodiment includes in step S30: Step S301: determining a thematic layer according to the layer structure.

[0054] It should be noted that the layer structure is first extracted to extract the thematic layer. In the system construction process of this embodiment, the layer management function of the map engine is realized through a self-developed algorithm, and at the same time, the layer management function meets the WMS standard.

[0055] Step S302: Slice the thematic layer to obtain a layer slicing result.

[0056] It should be understood that based on the layer management function, the slicing function of the thematic layer is realized. When the map function is called on the front end, all thematic layer operations are performed on the GIS server. The scalable computing advantages of the server can be used on the server side to greatly improve the computing efficiency. On the WEB side, it is only necessary to load the thematic map slices according to the rules, without excessive calculations. This greatly improves the display efficiency of the system.

[0057] Step S303: performing coordinate transformation on the layer slicing result to obtain transformation coordinate information.

[0058] In the specific implementation, the map coordinate system used in the system is Web Mercator, which is the same as the existing public maps, and is a projection coordinate system. In order to apply this technology to a wider range of fields, this proposal implements the projection conversion algorithm of the commonly used domestic coordinate system in this system, so that the proposed algorithm can support the commonly used coordinate system released by the country. For the following coordinate system conversion process, the source coordinate system and the target coordinate system are based on the same geodetic datum (geodetic coordinate system), and the calculation method is as follows: The preset coordinate calculation formula is the Mercator coordinate calculation formula: (B, L) → (X, Y), standard latitude B0, origin latitude 0, origin longitude L0: Mercator projection reverse calculation formula: (X,Y) → (B,L), standard latitude B0, origin latitude 0, origin longitude L0: L=YE Where a - the major semi-axis of the ellipsoid; b - ellipsoid semi-minor axis; f - flattening (ab) / a; e - first eccentricity ; e'-second eccentricity ; N - radius of curvature of the cambered circle; R - radius of meridian curvature; B - latitude, L - longitude, unit is radian degree (RAD); X N -Vertical coordinate, Y E - Horizontal and rectangular coordinates, in meters (M).

[0059] In this way, accurate calculation and transformation coordinate information is achieved.

[0060] Furthermore, in order to prevent offset during the conversion process, after step S303, it also includes: performing basic coordinate correction on the layer slicing result to obtain basic correction information; calculating correction parameters based on the basic correction information; obtaining a correction algorithm based on the correction parameters, and optimizing the conversion coordinate information based on the correction algorithm.

[0061] It should be noted that, due to the widespread offset of map slices in the current basic base map slice service, the common practice is to perform correction conversion according to the entire layer, but this practice will lead to large errors after correction. In the solution of this embodiment, correction conversion is performed through personalized customized conversion parameters and independent correction algorithms, and the accuracy after conversion is controlled within 30CM, which fully meets the production environment of system application.

[0062] The conversion process is as follows: First, the basic coordinate correction is performed. The correction constants are: latitude correction 35 degrees to obtain the intermediate latitude parameter lat, longitude correction 105 degrees to obtain the intermediate longitude parameter lon, as the basic correction information.

[0063] Secondly, the latitude correction parameters latmidpara and lonmidpara are calculated through the intermediate parameters lat and lon: Finally, in the correction algorithm, in order to improve the accuracy of the calculation results, this system creates unique correction parameters radhat and magic, and then calculates the final latitude and longitude correction result parameters latlastpara and lonlastpara based on the correction parameters, as shown below: The final calculation formula based on the correction result is as follows: In this way, accurate correction is achieved and errors are reduced or prevented.

[0064] This embodiment determines the thematic layer according to the layer structure; slices the thematic layer to obtain the layer slicing result; and performs coordinate conversion on the layer slicing result to obtain conversion coordinate information. In this way, based on the layer management function, the spatial element slicing function of the thematic layer is realized. When the map function is called on the front end, all thematic layer operations are performed on the GIS server side. The server side can use the scalable computing advantages of the server side to greatly improve the computing efficiency; and realizes the projection conversion algorithm of the commonly used coordinate system, so that the layer management function of this embodiment can be widely used and promoted.

[0065] In addition, an embodiment of the present invention further provides a storage medium, on which an operation strategy generation program is stored. When the operation strategy generation program is executed by a processor, the steps of the operation strategy generation method described above are implemented.

[0066] Since the storage medium adopts all the technical solutions of all the above embodiments, it has at least all the beneficial effects brought by the technical solutions of the above embodiments, which will not be described one by one here.

[0067] Reference Figure 7 , Figure 7 This is a structural block diagram of the first embodiment of the operation strategy generating device of the present invention.

[0068] like Figure 7 As shown, the operation strategy generating device proposed in the embodiment of the present invention includes: The layer generation module 10 is used to obtain spatial service data and generate a service data layer according to the spatial service data; A layer layering module 20, used for layering the business data layer to obtain multiple layer structures; A coordinate conversion module 30 is used to slice and convert the layer structure to obtain conversion coordinate information; The strategy generation module 40 is used to obtain government-enterprise distribution information according to the converted coordinate information and a preset spatial analysis model, and to generate a market operation strategy according to the government-enterprise distribution information.

[0069] In this embodiment, spatial business data is obtained, and a business data layer is generated based on the spatial business data; the business data layer is layered to obtain multiple layer structures; the layer structure is sliced ​​and coordinate converted to obtain conversion coordinate information; government and enterprise distribution information is obtained based on the conversion coordinate information and a preset spatial analysis model, and a market operation strategy is generated based on the government and enterprise distribution information. In this way, the generation, layering and slicing of layers based on spatial business data are realized, and then coordinate conversion is performed. Since the process of spatial resource calculation is calculated through the back-end server, the calculation efficiency is greatly improved, and it is finally displayed on the WEB side in the form of compressed images, which does not need to occupy too many WEB resources, and only needs to be loaded and displayed, which effectively improves the system loading efficiency and user perception, and the market operation strategy finally assisted in generating is more intuitive and convenient.

[0070] In one embodiment, the coordinate conversion module 30 is further used to determine the thematic layer according to the layer structure; slice the thematic layer to obtain a layer slicing result; and perform coordinate conversion on the layer slicing result to obtain conversion coordinate information.

[0071] In one embodiment, the coordinate transformation module 30 is further used to perform basic coordinate correction on the layer slicing result to obtain basic correction information; calculate correction parameters based on the basic correction information; obtain a correction algorithm based on the correction parameters, and optimize the transformed coordinate information based on the correction algorithm.

[0072] In one embodiment, the coordinate transformation module 30 is also used to obtain a preset coordinate calculation formula and a projection reverse calculation formula; the layer slicing result is coordinate transformed based on the geodetic coordinate system through the preset coordinate calculation formula and the projection reverse calculation formula to obtain the transformed coordinate information.

[0073] In one embodiment, the policy generation module 40 is further used to determine the location grid information according to the converted coordinate information; calculate the government-enterprise aggregation degree according to the location grid information and the spatial business data; and determine the government-enterprise distribution information according to the government-enterprise aggregation degree.

[0074] In one embodiment, the policy generation module 40 is also used to determine the distribution positions of government and enterprise users in each grid based on the location grid information; calculate the proximity of government and enterprise users based on the distribution positions of government and enterprise users and the spatial business data; and obtain the government and enterprise aggregation degree based on the proximity of government and enterprise users.

[0075] In one embodiment, the strategy generation module 40 is further used to determine key grids based on the government and enterprise distribution information and the location grid information; predict grid business types based on the key grids and the business attribute information; and generate market operation strategies based on the grid business types.

[0076] It should be understood that the above is only an example and does not constitute any limitation on the technical solution of the present invention. In specific applications, technicians in this field can make settings as needed, and the present invention does not limit this.

[0077] It should be noted that the workflow described above is merely illustrative and does not limit the scope of protection of the present invention. In practical applications, technicians in this field can select part or all of them according to actual needs to achieve the purpose of the present embodiment, and no limitation is made here.

[0078] In addition, for technical details not fully described in this embodiment, reference can be made to the operation strategy generating method provided in any embodiment of the present invention, and will not be repeated here.

[0079] In addition, it should be noted that, in this article, the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, article or system including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or system. In the absence of further restrictions, an element defined by the sentence "comprises a ..." does not exclude the existence of other identical elements in the process, method, article or system including the element.

[0080] The serial numbers of the above embodiments of the present invention are only for description and do not represent the advantages or disadvantages of the embodiments.

[0081] Through the description of the above implementation methods, those skilled in the art can clearly understand that the above-mentioned embodiment methods can be implemented by means of software plus a necessary general hardware platform, and of course by hardware, but in many cases the former is a better implementation method. Based on such an understanding, the technical solution of the present invention is essentially or the part that contributes to the prior art can be embodied in the form of a software product, which is stored in a storage medium (such as a read-only memory (ROM) / RAM, a magnetic disk, or an optical disk), and includes a number of instructions for a terminal device (which can be a mobile phone, a computer, a server, or a network device, etc.) to execute the methods described in each embodiment of the present invention.

[0082] The above are only preferred embodiments of the present invention, and are not intended to limit the patent scope of the present invention. Any equivalent structure or equivalent process transformation made using the contents of the present invention specification and drawings, or directly or indirectly applied in other related technical fields, are also included in the patent protection scope of the present invention.

Claims

1. A method for generating an operation strategy, characterized in that: The operation strategy generation method comprises: Acquire spatial business data, and generate a business data layer according to the spatial business data; Layering the business data layer to obtain multiple layer structures; Slicing and coordinate conversion of the layer structure to obtain conversion coordinate information; The government-enterprise distribution information is obtained according to the converted coordinate information and a preset spatial analysis model, and a market operation strategy is generated according to the government-enterprise distribution information.

2. The method for generating an operation strategy according to claim 1, characterized in that: The slicing and coordinate conversion of the layer structure to obtain conversion coordinate information includes: Determine the thematic layer according to the layer structure; Slicing the thematic layer to obtain a layer slicing result; The layer slicing result is subjected to coordinate transformation to obtain transformation coordinate information.

3. The method for generating an operation strategy according to claim 2, characterized in that: After performing coordinate transformation on the layer slicing result to obtain transformation coordinate information, the method further includes: Performing basic coordinate correction on the layer slicing result to obtain basic correction information; Calculate correction parameters according to the basic correction information; A correction algorithm is obtained according to the correction parameters, and the conversion coordinate information is optimized according to the correction algorithm.

4. The method for generating an operation strategy according to claim 2, wherein: The performing coordinate transformation on the layer slicing result to obtain transformation coordinate information includes: Get the preset coordinate calculation formula and projection reverse calculation formula; The layer slicing result is subjected to coordinate transformation based on the geodetic coordinate system by using the preset coordinate calculation formula and the projection reverse calculation formula to obtain transformation coordinate information.

5. The method for generating an operation strategy according to claim 1, wherein: The obtaining of government and enterprise distribution information according to the converted coordinate information and the preset spatial analysis model includes: Determine position grid information according to the converted coordinate information; Calculate the government-enterprise aggregation degree according to the location grid information and the spatial business data; The government-enterprise distribution information is determined according to the government-enterprise concentration degree.

6. The method for generating an operation strategy according to claim 5, characterized in that: The calculating the government-enterprise aggregation degree according to the location grid information and the spatial business data includes: Determine the distribution location of government and enterprise users in each grid according to the location grid information; Calculate the proximity of government and enterprise users according to the distribution locations of the government and enterprise users and the spatial service data; The government-enterprise aggregation degree is obtained according to the government-enterprise user proximity degree.

7. The method for generating an operation strategy according to claim 6, characterized in that: Generating a market operation strategy according to the government-enterprise distribution information includes: Determine a key grid according to the government and enterprise distribution information and the location grid information; Predicting a grid service type according to the key grid and the service attribute information; A market operation strategy is generated according to the grid service type.

8. An operation strategy generating device, characterized in that: The operation strategy generating device comprises: A layer generation module, used to obtain spatial service data and generate a service data layer according to the spatial service data; A layer layering module, used for layering the business data layer to obtain multiple layer structures; A coordinate conversion module, used for slicing and coordinate conversion of the layer structure to obtain conversion coordinate information; A strategy generation module is used to obtain government-enterprise distribution information based on the converted coordinate information and a preset spatial analysis model, and to generate a market operation strategy based on the government-enterprise distribution information.

9. An operation strategy generating device, characterized in that: The operation strategy generation device comprises: a memory, a processor, and an operation strategy generation program stored in the memory and running on the processor, wherein the operation strategy generation program is configured to implement the operation strategy generation method according to any one of claims 1 to 7.

10. A storage medium, characterized in that: The storage medium stores an operation strategy generation program, and when the operation strategy generation program is executed by the processor, the operation strategy generation method according to any one of claims 1 to 7 is implemented.

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