Land supply data management system and method based on cloud platform

Abstract

The invention discloses a land supply data management system and method based on a cloud platform, and relates to the technical field of land supply data management, and the method comprises the steps: analyzing the land development and land inventory conditions in a region, and evaluating the land supply and demand conditions in the region; acquiring land supply data of the region in different historical land supply records and collecting the land supply data to obtain a land supply data set, evaluating the approximation degree of the region and other regions in land supply conditions, and obtaining a target region; performing anomaly evaluation on the land supply condition of the region to obtain an abnormal region; according to the method, abnormal root cause analysis is carried out on an abnormal region to obtain abnormal root cause data, and land supply abnormity early warning is sent to management personnel of the abnormal region through a cloud platform, so that the accuracy of abnormal early warning of land supply conditions in the region is improved, and land supply abnormity in the region can be quickly and accurately found; and the efficiency of land supply management in the region can be improved.

Description

Technical Field

[0001] The present invention relates to the technical field of land supply data management, and in particular to a land supply data management system and method based on a cloud platform. Background Art

[0002] Land supply refers to the process in which relevant departments provide land to the market through various means, and it plays an important role in aspects such as urban development and agricultural production. Therefore, it is very important to manage land supply data. The benefits of managing land supply data include but are not limited to the following points: 1. Avoid land waste. By analyzing and processing land supply data, the land supply and demand situation in different regions can be understood, so as to dynamically adjust the land supply strategy and avoid waste of land resources; 2. Improve land governance efficiency. Through land supply data, the changing trend of land supply and demand in different regions can be understood, providing a strong basis for the land governance of government departments; 3. Reduce land use costs. By effectively analyzing land supply data, the best land use areas can be found for enterprises, which can effectively reduce the land use costs of enterprises.

[0003] The traditional way to manage land supply data is mainly to manually input land supply data. This way will result in a high error rate. The relevant data of land supply collected in different regions or even different institutions are distributed and stored in isolated systems, and the data cannot be effectively connected. And currently, there is no effective method to monitor land supply behavior to accurately conduct risk early warning and root cause analysis of land supply, which will seriously reduce the efficiency of land supply management. Summary of the Invention

[0004] The purpose of the present invention is to provide a land supply data management system and method based on a cloud platform to solve the problems raised in the prior art.

[0005] To achieve the above purpose, the present invention provides the following technical solution: A land supply data management method based on a cloud platform, the method includes: Step S100: Obtain the historical land supply records in the region, analyze the land development and land inventory status in the region, and evaluate the land supply and demand status in the region to obtain land supply data; Step S200: Obtain the land supply data in different historical land supply records in the region and gather them to obtain a land supply data set, obtain the characteristic land supply data sets of other regions, evaluate the similarity degree of the land supply status between the region and other regions to obtain the target region; Step S300: Obtain the historical land supply anomaly data of the target area, monitor the land supply situation in the area during the current period, and combine the historical land supply anomaly data and the characteristic land supply data set to evaluate the land supply status of the area for anomalies and obtain the anomaly area; Step S400: Conduct an analysis of the root cause of the anomaly in the anomaly area to obtain the root cause data of the anomaly, send a land supply anomaly warning to the management personnel in the anomaly area through the cloud platform, and push the root cause data of the anomaly to the management personnel.

[0006] Furthermore, step S100 includes: Step S101: Obtain the historical land supply records of the area, and based on the historical land supply records, analyze the land development status in the area. The specific analysis process is as follows: Obtain the actual total development area and actual development duration of each land development project in the area from the historical land supply records, and obtain the planned total development area and planned total development duration of each land development project from the cloud platform; Calculate the land development efficiency η of the area in the historical land supply records: , where j is the total number of each land development project; A´ （i,sum） is the actual total development area of the i-th land development project in the area in the historical land supply records; A （i,sum） is the planned total development area of the i-th land development project in the area; T´ （i,sum） is the actual development duration of the i-th land development project in the area in the historical land supply records; T （i,sum） is the planned total development duration of the i-th land development project in the area in the historical land supply records; Step S102: Based on the historical land supply records, analyze the land inventory status in the area. Specifically: Obtain the total housing sales area B sum and the total land inventory area C sum in the area from the historical land supply records, and calculate the land inventory pressure α = C sum / B sum ; Step S103: Based on the historical land supply records, evaluate the land supply and demand status in the area. The specific evaluation process is as follows: Obtain the population p, gross domestic product G, consumer price index CPT, and the number of housing sales D sum in the area from the historical land supply records, and calculate the land demand index Q = β · p · (G / CPT) + γ · D sum, where β and γ are the first weight coefficient and the second weight coefficient, respectively; Step S104: Obtain the total land supply area S of the region from the historical land supply records sum , obtain the average development cycle k of the land in the region, and calculate the predicted land demand B in the region in the historical land supply records k sum : , where τ is the land demand growth rate; Calculate the land supply - demand deviation degree H = S sum / B k sum ; Step S105: Aggregate the land development efficiency η, land inventory pressure α, land demand index Q, and land supply - demand deviation degree H in the region in the historical land supply records, and use them as the values of the respective land supply indicators in the region in the historical land supply records to obtain the land supply data in the region in the historical land supply records.

[0007] Further, step S200 includes: Step S201: Obtain the land supply data of the region in each historical land supply record, and obtain the values of the respective land supply indicators in the region from the land supply data; Obtain the values of the respective land supply indicators in the region in each historical land supply record and aggregate them to obtain the land supply data set of the region, where the region contains only a single historical land supply record in a single historical period; Step S202: Obtain the characteristic land supply data set of other regions from the cloud platform, where the characteristic land supply data set includes the values of the respective land supply indicators of other regions in several historical periods; Step S203: Obtain the preset reference values of the respective land supply indicators from the cloud platform, perform data pre - processing on the land supply data set and the characteristic land supply data set respectively, and calculate the distance value L between an element in the land supply data set and another element in the characteristic land supply data set: , where n is the total number of the respective land supply indicators, Z X is the value of the x - th land supply indicator in a certain element; Z´ X is the value of the x - th land supply indicator in another element; Z ▽ is the preset reference value of the x - th land supply indicator in the cloud platform; Step S204: Obtain the total number ψ of different elements in the land supply data set, obtain the preset eigenvalue ζ, and obtain the minimum value of the sum of the distance values between the last ζ elements in the land supply data set and several adjacent ζ elements in the characteristic land supply data set, where the total number of elements included between the last element of several adjacent ζ elements and the first element in the characteristic land supply data set is not less than the total number ψ - 1; Step S205: Obtain a certain adjacent ζ elements corresponding to the minimum value, and intercept and collect the last element of a certain adjacent ζ elements and the first ψ - 1 elements before the last element of a certain adjacent ζ elements from the characteristic land supply data set to obtain the marked land supply data set corresponding to the land supply data set of the region in other regions; Calculate the land supply difference value W between the region and other regions: , where, L´ v is the distance value between the v-th element in the land supply data set and the v-th element in the marked land supply data set; When the land supply difference value W is less than the preset difference threshold, it is determined that the land supply situation between the region and other regions is approximate, and other regions are recorded as the target regions of the region.

[0008] Further, step S300 includes: Step S301: Obtain each target region of the region, obtain the historical land supply abnormal data of each target region, and obtain the land supply abnormal score evaluated by a professional institution for the target region of the region in several historical periods from the historical land supply abnormal data; Step S302: Monitor the land supply situation of the region in the current period, obtain the values of various land supply indicators of the region in the current period, and obtain the characteristic land supply data set of the target region; Step S303: Calculate the distance value between each element in the characteristic land supply data set of the region and the target region in the current period, and obtain the minimum value of the distance values between each element in the characteristic land supply data set of the region and the target region. When the minimum value of the distance value is less than the preset characteristic distance value, mark the target region and record it as the marked target region, and obtain the historical period corresponding to the minimum value of the distance value in the marked target region, and record it as the characteristic historical period corresponding to the target region and the region; Step S304: Obtain the land supply anomaly score of the marked target area in the characteristic historical period from the historical land supply anomaly data, and record it as the reference land supply anomaly score of the marked target area for the area in the current period; Step S305: Obtain the reference land supply anomaly scores of several marked target areas for the area in the current period, calculate the average value of the reference land supply anomaly scores of several marked target areas for the area in the current period, and use it as the land supply anomaly score of the area in the current period. When the land supply anomaly score of the area in the current period is greater than the preset anomaly score threshold, it is determined that the land supply in the current period of the area is abnormal, and the area in the current period is recorded as an abnormal area.

[0009] Further, step S400 includes: Step S401: Conduct an analysis of the root cause of the anomaly for the abnormal areas in the cloud platform. The specific analysis process is as follows: Obtain several marked target areas of the abnormal area in the current period, and obtain the characteristic historical periods corresponding to the several marked target areas and the abnormal area; Step S402: Obtain a certain root cause of the anomaly obtained through the evaluation of a professional institution for the historical land supply anomaly data of the marked target area of the abnormal area in the characteristic historical period, and record it as the reference root cause of the anomaly of the marked target area for the abnormal area; Step S403: Set a value u, obtain the reference root causes of the anomaly of several marked target areas for the abnormal area, divide the total number of marked target areas corresponding to each reference root cause of the anomaly by the total number of several marked target areas to obtain the root cause proportion of each reference root cause of the anomaly, select the top u reference root causes of the anomaly in terms of root cause proportion as the target root causes of the anomaly of the abnormal area in the current period, and collect them to obtain the root cause data of the abnormal area; Step S404: Obtain the management account of the manager of the abnormal area through the cloud platform, send a land supply anomaly warning for the abnormal area to the management account, and push the root cause data of the abnormal area of the abnormal area to the management account through the cloud platform; In the above steps, the analysis of the root cause of the anomaly for the abnormal area is because issuing an anomaly warning for the land supply status in the abnormal area can only serve as a reminder notice. To quickly and effectively solve the problem of land supply anomaly, it is necessary to accurately know the root cause of the anomaly that leads to the land supply anomaly. Therefore, obtaining the target root cause of the anomaly in the abnormal area can not only accurately understand the land supply anomaly situation, but also further improve the efficiency of solving the land supply anomaly problem.

[0010] In order to better implement the above method, a land supply data management system based on a cloud platform is also proposed. The system includes a land supply status evaluation module, a land supply approximate evaluation module, a land supply anomaly evaluation module, and an anomaly warning module; The land supply status evaluation module is used to analyze the land development and land inventory status in a region, evaluate the land supply and demand status in the region, and obtain land supply data; The land supply approximate evaluation module is used to evaluate the approximation degree of the land supply status between a region and other regions, and obtain the target region; The land supply anomaly evaluation module is used to monitor the land supply situation in the region during the current period, and conduct an anomaly evaluation of the land supply status in the region to obtain the anomaly region; The anomaly warning module is used to send a land supply anomaly warning to the management personnel in the anomaly region through the cloud platform, and push information about the anomaly root cause data in the anomaly region.

[0011] Furthermore, the land supply status evaluation module includes a land supply status evaluation unit; The land supply status evaluation unit is used to obtain the historical land supply records in the region, analyze the land development and land inventory status in the region, and evaluate the land supply and demand status in the region to obtain land supply data.

[0012] Furthermore, the land supply approximate evaluation module includes a data acquisition unit and a land supply approximate evaluation unit; The data acquisition unit is used to obtain the land supply data in each historical land supply record in the region, obtain the land supply data set of the region, and obtain the characteristic land supply data set of other regions; The land supply approximate evaluation unit is used to evaluate the approximation degree of the land supply status between a region and other regions, and obtain the target region of the region.

[0013] Furthermore, the land supply anomaly evaluation module includes a land supply anomaly scoring unit and a land supply anomaly evaluation unit; The land supply anomaly scoring unit is used to obtain the historical land supply anomaly data of each target region in the region, monitor the land supply situation in the region during the current period, and calculate the land supply anomaly score in the region during the current period; The land supply anomaly evaluation unit is used to conduct an anomaly evaluation of the land supply status in the region according to the land supply anomaly score to obtain the anomaly region.

[0014] Furthermore, the anomaly warning module includes a root cause analysis unit and an anomaly warning unit; A root cause analysis unit for performing root cause analysis on an abnormal area to obtain root cause data of the abnormality; An abnormal warning unit for issuing a land supply abnormality warning for the abnormal area through a cloud platform and pushing the root cause data of the abnormality to the management personnel of the abnormal area.

[0015] Compared with the prior art, the beneficial effects of the present invention are as follows: The present invention realizes the intelligent management of land supply by using land supply data. Through the cloud platform, the relevant data of land supply collected from different regions or even different institutions can be uniformly stored, enabling the intercommunication of land supply data. The land supply data within the region is monitored and analyzed, so as to effectively issue an abnormality warning for the land supply situation within the region and accurately evaluate the root cause of the abnormality in the land supply situation within the region. This not only enables the rapid and accurate discovery of land supply abnormalities within the region, but also greatly improves the efficiency of land supply management within the region. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 is a flowchart of a method for managing land supply data based on a cloud platform according to the present invention; Figure 2 is a schematic diagram of modules of a land supply data management system based on a cloud platform according to the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0017] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all of the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0018] Embodiment: As Figure 1 - Figure 2 shown, the present invention provides a technical solution, a method for managing land supply data based on a cloud platform, and the method includes: Step S100: Obtain the historical land supply records in the region, analyze the land development and land inventory status in the region, and evaluate the land supply and demand status in the region to obtain land supply data; Among them, step S100 includes: Step S101: Obtain the historical land supply records in the region, and based on the historical land supply records, analyze the land development status in the region. The specific analysis process is as follows: Obtain the actual total development area and actual development duration of each land development project in the region from the historical land supply records, and obtain the planned total development area and planned total development duration of each land development project from the cloud platform; Calculate the land development efficiency η of the area in the historical land supply record: , where j is the total number of each land development project; A´ （i,sum） is the actual total development area of the i-th land development project in the area in the historical land supply record; A （i,sum） is the planned total development area of the i-th land development project in the area; T´ （i,sum） is the actual development duration of the i-th land development project in the area in the historical land supply record; T （i,sum） is the planned total development duration of the i-th land development project in the area in the historical land supply record; Step S102: Analyze the land inventory status in the area based on the historical land supply record. Specifically: Obtain the total housing sales area B sum and the total land inventory area C sum in the area from the historical land supply record, and calculate the land inventory pressure α = C sum / B sum ; For example, if the total land inventory area C sum is 100 square kilometers; and the total housing sales area B sum is 20 square kilometers, calculate the land inventory pressure α = C sum / B sum = 100 / 20 = 5; Step S103: Evaluate the land supply and demand status in the area based on the historical land supply record. The specific evaluation process is as follows: Obtain the population p, gross domestic product G, consumer price index CPT, and the number of housing sales D sum in the area from the historical land supply record, and calculate the land demand index Q = β·p·(G / CPT)+γ·D sum , where β and γ are the first weight coefficient and the second weight coefficient respectively; For example, β and γ can be estimated by the least squares method using a preset driving model; Step S104: Obtain the total land supply area S sum in the area from the historical land supply record, obtain the average development cycle k of the land in the area, and calculate the predicted land demand B k sum in the area in the historical land supply record: , where τ is the land demand growth rate; For example, the specific formula for τ is: , where B -k sum is the total housing sales area in the region of a certain historical land supply record whose time interval from the historical land supply record is the average development cycle k; Calculate the land supply - demand deviation degree H of the region in the historical land supply record: H = S sum / B k sum ; Step S105: Aggregate the land development efficiency η, land inventory pressure α, land demand index Q, and land supply - demand deviation degree H of the region in the historical land supply record, and use them as the values of various land supply indicators of the region in the historical land supply record to obtain the land supply data of the region in the historical land supply record; Step S200: Obtain the land supply data of the region in different historical land supply records and aggregate them to obtain a land supply data set, obtain the characteristic land supply data sets of other regions, evaluate the approximation degree of the region and other regions in terms of land supply status, and obtain the target region; Among them, step S200 includes: Step S201: Obtain the land supply data of the region in each historical land supply record, and obtain the values of various land supply indicators in the region from the land supply data; Obtain the values of various land supply indicators of the region in each historical land supply record and aggregate them to obtain the land supply data set of the region. Among them, the region contains only a single historical land supply record in a single historical period; Step S202: Obtain the characteristic land supply data sets of other regions from the cloud platform. Among them, the characteristic land supply data set includes the values of various land supply indicators of other regions in several historical periods; Step S203: Obtain the preset reference values of various land supply indicators from the cloud platform, perform data pre - processing on the land supply data set and the characteristic land supply data set respectively, and calculate the distance value L between an element in the land supply data set and another element in the characteristic land supply data set: , where n is the total number of various land supply indicators, Z X is the value of the x - th land supply indicator in a certain element; Z´ X is the value of the x - th land supply indicator in another element; Z ▽ is the preset reference value of the x - th land supply indicator in the cloud platform; For example, the pre - processing in the data pre - processing of the land supply data set and the characteristic land supply data set is standardization processing and normalization processing; Step S204: Obtain the total number ψ of different elements in the land supply data set, obtain the preset eigenvalue ζ, and obtain the minimum value of the sum of the distance values between the last ζ elements in the land supply data set and several adjacent ζ elements in the characteristic land supply data set, where the total number of elements included between the last element of several adjacent ζ elements and the first element in the characteristic land supply data set is not less than the total number ψ - 1; Step S205: Obtain a certain adjacent ζ elements corresponding to the minimum value, and intercept and collect the last element of a certain adjacent ζ elements and the first ψ - 1 elements before the last element of a certain adjacent ζ elements from the characteristic land supply data set to obtain the marked land supply data set corresponding to the land supply data set of the region in other regions; Calculate the land supply difference value W between the region and other regions: , where, L´ v is the distance value between the v-th element in the land supply data set and the v-th element in the marked land supply data set; For example, ψ is 3; L´1 is 0.7; L´2 is 0.8; L´3 is 0.6; calculate the land supply difference value W between the region and other regions = 0.7 + 0.8 + 0.6 = 2.1; When the land supply difference value W is less than the preset difference threshold, it is determined that the land supply situation between the region and other regions is approximately the same, and other regions are recorded as the target regions of the region; Step S300: Obtain the historical land supply abnormal data of the target region, monitor the land supply situation of the region in the current period, and combine the historical land supply abnormal data and the characteristic land supply data set to perform an abnormal assessment on the land supply situation of the region to obtain the abnormal region; Among them, Step S300 includes: Step S301: Obtain each target region of the region, obtain the historical land supply abnormal data of each target region, and obtain the land supply abnormal score evaluated by a professional institution for the target region of the region in several historical periods from the historical land supply abnormal data; Step S302: Monitor the land supply situation of the region in the current period, obtain the values of various land supply indicators of the region in the current period, and obtain the characteristic land supply data set of the target region; Step S303: Calculate the distance values between the area in the current period and each element in the characteristic land supply dataset of the target area, and obtain the minimum value of the distance values between the area and each element in the characteristic land supply dataset of the target area. When the minimum value of the distance values is less than the preset characteristic distance value, mark the target area and denote it as the marked target area, and obtain the historical period corresponding to the marked target area where the minimum value of the distance value is located, and denote it as the characteristic historical period corresponding to the target area and the area; Step S304: Obtain the land supply anomaly score of the marked target area in the characteristic historical period from the historical land supply anomaly data, and denote it as the reference land supply anomaly score of the marked target area for the area in the current period; Step S305: Obtain the reference land supply anomaly scores of several marked target areas for the area in the current period, calculate the average value of the reference land supply anomaly scores of several marked target areas for the area in the current period, and use it as the land supply anomaly score of the area in the current period; When the land supply anomaly score of the area in the current period is greater than the preset anomaly score threshold, it is determined that the land supply of the area in the current period is abnormal, and the area in the current period is denoted as the abnormal area; Step S400: Conduct an analysis of the root cause of the anomaly for the abnormal area to obtain the root cause data of the anomaly, send a land supply anomaly warning to the management personnel of the abnormal area through the cloud platform, and push the root cause data of the anomaly to the management personnel; Among them, Step S400 includes: Step S401: Conduct an analysis of the root cause of the anomaly for the abnormal area in the cloud platform. The specific analysis process is as follows: Obtain several marked target areas of the abnormal area in the current period, and obtain the characteristic historical periods corresponding to several marked target areas and the abnormal area; Step S402: Obtain a certain root cause of the anomaly obtained through professional institution evaluation during the characteristic historical period of the historical land supply anomaly data of the marked target area of the abnormal area, and denote it as the reference root cause of the anomaly of the marked target area for the abnormal area; For example, each root cause of the land supply anomaly includes a reduction in the planned land supply volume, an extension of the land approval cycle, a decrease in housing prices, etc.; Step S403: Set a value u, obtain the reference root causes of the anomaly of several marked target areas for the abnormal area, divide the total number of marked target areas corresponding to each reference root cause of the anomaly by the total number of several marked target areas to obtain the root cause proportion of each reference root cause of the anomaly, select the top u reference root causes of the anomaly with the root cause proportion as the target root cause of the anomaly of the abnormal area in the current period, and collect them to obtain the root cause data of the anomaly of the abnormal area; Step S404: Obtain the management account of the management personnel in the abnormal area through the cloud platform, send an early warning of abnormal land supply in the abnormal area to the management account, and push the abnormal root cause data of the abnormal area to the management account through the cloud platform; To better implement the above method, a land supply data management system based on the cloud platform is also proposed. The system includes a land supply status evaluation module, a land supply approximate evaluation module, a land supply abnormal evaluation module, and an abnormal early warning module; The land supply status evaluation module is used to analyze the land development and land inventory status in the area, evaluate the land supply and demand status in the area, and obtain land supply data; The land supply approximate evaluation module is used to evaluate the approximation degree of the area and other areas in terms of land supply status, and obtain the target area; The land supply abnormal evaluation module is used to monitor the land supply situation in the area during the current period, and conduct an abnormal evaluation of the land supply status in the area to obtain the abnormal area; The abnormal early warning module is used to send an early warning of abnormal land supply to the management personnel in the abnormal area through the cloud platform, and push information on the abnormal root cause data of the abnormal area; Among them, the land supply status evaluation module includes a land supply status evaluation unit; The land supply status evaluation unit is used to obtain the historical land supply records in the area, analyze the land development and land inventory status in the area, and evaluate the land supply and demand status in the area to obtain land supply data; Among them, the land supply approximate evaluation module includes a data acquisition unit and a land supply approximate evaluation unit; The data acquisition unit is used to obtain the land supply data of the area in each historical land supply record, obtain the land supply data set of the area, and obtain the characteristic land supply data set of other areas; The land supply approximate evaluation unit is used to evaluate the approximation degree of the area and other areas in terms of land supply status, and obtain the target area of the area; Among them, the land supply abnormal evaluation module includes a land supply abnormal scoring unit and a land supply abnormal evaluation unit; The land supply abnormal scoring unit is used to obtain the historical land supply abnormal data of each target area in the area, monitor the land supply situation in the area during the current period, and calculate the land supply abnormal score in the area during the current period; The land supply abnormal evaluation unit is used to conduct an abnormal evaluation of the land supply status in the area according to the land supply abnormal score, and obtain the abnormal area; Among them, the abnormal early warning module includes a root cause analysis unit and an abnormal early warning unit; A root cause analysis unit, configured to perform root cause analysis on an abnormal area to obtain root cause data of the abnormality; An abnormal warning unit, configured to issue a land supply abnormal warning for the abnormal area through a cloud platform and push the root cause data of the abnormality to the management personnel of the abnormal area.

[0019] For those skilled in the art, it is obvious that the present invention is not limited to the details of the above exemplary embodiments, and without departing from the spirit or basic characteristics of the present invention, the present invention can be implemented in other specific forms. Therefore, from any point of view, the embodiments should be regarded as exemplary and non-limiting. The scope of the present invention is defined by the appended claims rather than the above description. Therefore, all changes falling within the meaning and scope of the equivalent elements of the claims are intended to be embraced within the present invention. Any reference signs in the claims should not be regarded as limiting the claims involved.

Claims

1. A method for managing land supply data based on a cloud platform, characterized in that The method includes: Step S100: Obtain the historical land supply records in the area, analyze the land development and land inventory status in the area, and evaluate the land supply and demand status in the area to obtain land supply data; Step S200: Obtain and collect the land supply data in the area within different historical land supply records to obtain a land supply data set, obtain the characteristic land supply data sets of other areas, evaluate the similarity degree of the land supply status between the area and the other areas to obtain a target area; Step S300: Obtain the historical land supply abnormal data of the target area, monitor the land supply situation in the area during the current period, and combine the historical land supply abnormal data and the characteristic land supply data set to conduct an abnormal evaluation of the land supply status in the area to obtain an abnormal area; Step S400: Conduct an analysis of the root cause of the abnormality in the abnormal area to obtain root cause of abnormality data, send a land supply abnormality warning to the management personnel in the abnormal area through the cloud platform, and push the root cause of abnormality data to the management personnel.

2. The method for managing land supply data based on a cloud platform according to claim 1, wherein, The said step S100 includes: Step S101: Obtain the historical land supply records in the area, and based on the historical land supply records, analyze the land development status in the area. The specific analysis process is as follows: Obtain the actual total development area and actual development duration of each land development project in the area from the historical land supply records, and obtain the planned total development area and planned total development duration of each land development project from the cloud platform; Calculate the land development efficiency η of the area in the historical land supply records: ， where j is the total number of all the land development projects; A´ （i,sum） is the actual total development area of the i-th land development project in the region in the historical land supply record; A （i,sum） is the planned total development area of the i-th land development project in the region; T´ （i,sum） is the actual development duration of the i-th land development project in the region in the historical land supply record; T （i,sum） is the planned total development duration of the i-th land development project in the region in the historical land supply record; Step S102: Analyze the land inventory status in the area based on the historical land supply records, specifically: Obtain the total housing sales area B within the area from the historical land supply records sum and the total land inventory area C sum , calculate the land inventory pressure α = C sum / B sum ; Step S103: Based on the historical land supply records, evaluate the land supply and demand status in the area. The specific evaluation process is as follows: Obtain the population quantity p, the gross production value G, the consumer price index CPT, and the number of housing sales D in the region from the historical land supply records sum , calculate the land demand index Q = β·p·(G / CPT) + γ·D in the region in the historical land supply records sum , where β and γ are the first weight coefficient and the second weight coefficient respectively; Step S104: Obtain the total land supply area S of the region from the historical land supply records sum , obtain the average development cycle k of the land in the region, and calculate the predicted land demand B of the region in the historical land supply records k sum : ， where τ is the land demand increase rate; Calculate the land supply-demand deviation H = S of the region in the historical land supply records sum / B k sum ; Step S105: Collect the land development efficiency η, land inventory pressure α, land demand index Q, and land supply and demand deviation degree H of the area in the historical land supply records, and use them as the values of the land supply indicators of the area in the historical land supply records to obtain the land supply data of the area in the historical land supply records.

3. The method for managing land supply data based on a cloud platform according to claim 2, wherein, The said step S200 includes: Step S201: Obtain the land supply data in the area within each historical land supply record, and obtain the values of the land supply indicators in the area from the land supply data; Obtain and collect the values of the land supply indicators in the area within each historical land supply record to obtain the land supply data set of the area. Among them, there is only a single historical land supply record in the area within a single historical period; Step S202: Obtain the characteristic land supply data sets of other areas from the cloud platform. Among them, the characteristic land supply data set includes the values of the land supply indicators in the other areas within several historical periods; Step S203: Obtain the preset reference values of the various land supply indicators from the cloud platform, perform data preprocessing on the land supply data set and the characteristic land supply data set respectively, and calculate the distance value L between an element in the land supply data set and another element in the characteristic land supply data set: ， where n is the total number of the above land supply indicators, and Z X is the value of the x-th land supply indicator in a certain element; Z' X is the value of the x-th land supply indicator in the other element; Z ▽ is the preset reference value of the x-th land supply indicator in the cloud platform; Step S204: Obtain the total number ψ of different elements in the land supply data set, obtain the preset characteristic value ζ, and obtain the minimum value of the sum of the distance values between the last ζ elements in the land supply data set and several adjacent ζ elements in the characteristic land supply data set, where the total number of elements included between the last element in the several adjacent ζ elements and the first element in the characteristic land supply data set is not less than the total number ψ - 1; Step S205: Obtain a certain adjacent ζ elements corresponding to the minimum value, and intercept and collect the last element of the certain adjacent ζ elements and the first ψ - 1 elements before the last element of the certain adjacent ζ elements from the characteristic land supply data set to obtain the marked land supply data set corresponding to the land supply data set of the region in the other region; Calculate the land supply difference value W between the region and the other region: ， where L´ v is the distance value between the v-th element in the land supply dataset and the v-th element in the marked land supply dataset; When the land supply difference value W is less than the preset difference threshold, it is determined that the land supply situations between the region and the other region are approximate, and the other region is recorded as the target region of the region.

4. The land supply data management method based on a cloud platform according to claim 3, characterized in that, The step S300 includes: Step S301: Obtain the respective target regions of the region, obtain the historical land supply abnormal data of the respective target regions, and obtain the land supply abnormal scores evaluated by professional institutions for the target regions of the region in several historical periods from the historical land supply abnormal data; Step S302: Monitor the land supply situation of the region in the current period, obtain the values of the various land supply indicators of the region in the current period, and obtain the characteristic land supply data set of the target region; Step S303: Calculate the distance values between each element in the characteristic land supply data sets of the region and the target region in the current period, and obtain the minimum value of the distance values between each element in the characteristic land supply data sets of the region and the target region. When the minimum value of the distance value is less than the preset characteristic distance value, mark the target region and record it as the marked target region, and obtain the historical period corresponding to the minimum value of the distance value in the marked target region, and record it as the characteristic historical period corresponding to the target region and the region; Step S304: Obtain the land supply anomaly score of the marked target area in the characteristic historical period from the historical land supply anomaly data, and record it as the reference land supply anomaly score of the marked target area for the area in the current period; Step S305: Obtain the reference land supply anomaly scores of several marked target areas for the area in the current period, calculate the average value of the reference land supply anomaly scores of the several marked target areas for the area in the current period, and use it as the land supply anomaly score of the area in the current period; When the land supply anomaly score of the area in the current period is greater than the preset anomaly score threshold, it is determined that the land supply in the area in the current period is abnormal, and the area in the current period is recorded as an abnormal area.

5. The land supply data management method based on a cloud platform according to claim 4, characterized in that The step S400 includes: Step S401: Conduct an abnormal root cause analysis on the abnormal areas in the cloud platform. The specific analysis process is as follows: Obtain several marked target areas of the abnormal areas in the current period, and obtain the characteristic historical periods corresponding to the several marked target areas and the abnormal areas; Step S402: Obtain a certain abnormal root cause obtained by professional institution evaluation of the historical land supply anomaly data of the marked target areas of the abnormal areas in the characteristic historical period, and record it as the reference abnormal root cause of the marked target areas for the abnormal areas; Step S403: Set a value u, obtain the reference abnormal root causes of the several marked target areas for the abnormal areas, divide the total number of marked target areas corresponding to each reference abnormal root cause by the total number of the several marked target areas to obtain the root cause proportion of each reference abnormal root cause, select the top u reference abnormal root causes with the root cause proportion as the target abnormal root causes of the abnormal areas in the current period, and collect them to obtain the abnormal root cause data of the abnormal areas; Step S404: Obtain the management account of the managers of the abnormal areas through the cloud platform, send a land supply anomaly warning to the management account for the abnormal areas, and push the abnormal root cause data of the abnormal areas to the management account through the cloud platform.

6. A land supply data management system based on a cloud platform, which is used to execute a land supply data management method based on a cloud platform according to any one of claims 1-5, characterized in that, The system includes a land supply status evaluation module, a land supply approximation evaluation module, a land supply anomaly evaluation module, and an abnormal warning module; The land supply status evaluation module is used to analyze the land development and land inventory status in the area, and evaluate the land supply and demand status in the area to obtain land supply data; The land supply approximation evaluation module is used to evaluate the approximation degree of the area and other areas in terms of land supply status to obtain the target area; The land supply anomaly evaluation module is used to monitor the land supply situation of the area in the current period and conduct an abnormal evaluation of the land supply status of the area to obtain abnormal areas; The abnormal warning module is used to send a land supply anomaly warning to the managers of the abnormal areas through the cloud platform and push information on the abnormal root cause data of the abnormal areas.

7. A land supply data management system based on a cloud platform according to claim 6, characterized in that, The land supply status evaluation module includes a land supply status evaluation unit; The land supply status evaluation unit is used to obtain the historical land supply records in the region, analyze the land development and land inventory status in the region, and evaluate the land supply and demand status in the region to obtain land supply data.

8. A land supply data management system based on a cloud platform according to claim 6, characterized in that The land supply approximate evaluation module includes a data acquisition unit and a land supply approximate evaluation unit; The data acquisition unit is used to obtain the land supply data of each historical land supply record in the region, obtain the land supply data set of the region, and obtain the characteristic land supply data set of other regions; The land supply approximate evaluation unit is used to evaluate the approximation degree of the land supply status between the region and the other regions to obtain the target region of the region.

9. The land supply data management system based on a cloud platform according to claim 6, characterized in that The land supply anomaly evaluation module includes a land supply anomaly scoring unit and a land supply anomaly evaluation unit; The land supply anomaly scoring unit is used to obtain the historical land supply anomaly data of each target region in the region, monitor the land supply situation in the region during the current period, and calculate the land supply anomaly score in the region during the current period; The land supply anomaly evaluation unit is used to perform an anomaly evaluation on the land supply status of the region according to the land supply anomaly score to obtain an anomaly region.

10. A land supply data management system based on a cloud platform according to claim 6, characterized in that, The anomaly warning module includes a root cause analysis unit and an anomaly warning unit; The root cause analysis unit is used to perform an anomaly root cause analysis on the anomaly region to obtain anomaly root cause data; The anomaly warning unit is used to send a land supply anomaly warning to the anomaly region through the cloud platform and push the anomaly root cause data to the management personnel of the anomaly region.

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