A data fusion management method based on multi-heterogeneous geographic information

Abstract

The present invention discloses a data fusion management method based on multivariate heterogeneous geographic information. The method utilizes a variety of hydrological information and Transformer technology to integrate and manage the status of large urban construction areas in different seasons and adjust the geographical location terrain changes. The method includes collecting different multivariate heterogeneous spatial data of urban construction areas, and the different multivariate heterogeneous spatial data include different urban construction areas at different altitudes geographical location terrain change types and different altitude hydrological information of urban construction areas within a preset time before the geographical location terrain changes occur. According to the statistics of hydrological information, the hydrological information at different altitudes of the urban construction area is classified to obtain the types of hydrological information in different seasons and the fusion conditions of the hydrological information types in the statistical area. The method ensures seasonal safety and accurate monitoring of the hydrological information per unit time of the urban construction area.

Description

Technical Field

[0001] The present invention relates to the field of data fusion of multi-heterogeneous geographic information in urban construction areas, and in particular to a data fusion management method based on multi-heterogeneous geographic information. Background Art

[0002] In the process of urban planning and construction, a large amount of multi-dimensional heterogeneous spatial data will be generated. These hydrological information data gradually show a trend of complexity and diversification. In particular, the planning of natural resource information in the process of urban construction is gradually refined, which requires the fusion and screening of diversified hydrological information data. However, in the process of continuous data updating, hydrological information data is constantly changing, and calculation errors occur in the extraction of specific data. It is impossible to characterize the complete specific geographic information data in the data's spatiotemporal state. This urgently requires technical personnel in this field to solve the corresponding technical problems. Summary of the invention

[0003] In order to solve the above technical problems, the present invention provides a method for integrating the status of large-scale urban construction areas in different seasons by utilizing multiple hydrological information and Transformer technology, realizing the integrated management of the status of large-scale urban construction areas in different seasons and adjusting the geographical location and terrain changes, thereby ensuring seasonal safety and accurate monitoring of the hydrological information per unit time of the urban construction areas.

[0004] In the initial aspect, the present invention provides a data fusion management method based on multi-heterogeneous geographic information, the method comprising:

[0005] Collecting different multivariate heterogeneous spatial data of urban construction areas, wherein the different multivariate heterogeneous spatial data include different types of terrain changes at different altitudes of different urban construction areas and hydrological information at different altitudes of urban construction areas within a preset time before the terrain changes at different altitudes occur;

[0006] The hydrological information at different altitudes in the urban construction area includes population distribution, water source distribution, temperature change range, rainfall, plant and animal species, population migration speed and religious beliefs in the urban construction area during operation;

[0007] Among them, the population distribution and water source distribution are collected per unit time, and the temperature change range, rainfall, animal and plant species, population migration speed and religious beliefs are collected according to the preset urban planning;

[0008] According to the hydrological information statistics, the hydrological information at different altitudes in the urban construction area is classified to obtain the types of hydrological information in different seasons in the statistical area and the fusion conditions of the hydrological information types. The types of hydrological information in different seasons in the statistical area include population distribution and water source distribution. The fusion conditions of the hydrological information types include temperature change range, rainfall, animal and plant species, population migration speed and religious beliefs.

[0009] The types of hydrological information in different seasons in the statistical area, the fusion conditions of hydrological information types, and the corresponding terrain change types at different altitudes in the urban construction area are uploaded to the Transformer algorithm to establish an algorithm for managing hydrological fluctuations caused by human activities and an algorithm for managing hydrological fluctuations caused by non-human activities.

[0010] The input of the algorithm for managing hydrological fluctuations caused by human activities is the types of hydrological information in different seasons in the statistical area, and the output is the management spatiotemporal sequence parameters of the algorithm for managing hydrological fluctuations caused by non-human activities; the input of the algorithm for managing hydrological fluctuations caused by non-human activities is the fusion conditions of the types of hydrological information and the determined spatiotemporal sequence parameters of management, and the output is the type of terrain change in the geographical location of the urban construction area;

[0011] In practical applications, the types of hydrological information in different seasons in the statistical area of ​​the urban construction area are collected per unit time, and input into the algorithm for managing hydrological fluctuations caused by human activities to obtain the governance spatiotemporal sequence parameters of the algorithm for managing hydrological fluctuations caused by non-human activities;

[0012] Compare the governance spatiotemporal sequence parameters of the non-human activity hydrological fluctuation governance algorithm with the preset spatiotemporal sequence length:

[0013] When the length of the governance space-time sequence parameter is less than the preset space-time sequence length, there is no need to set the fusion conditions of the hydrological information types, and the collection and analysis of the hydrological information types in different seasons in the statistical area should continue;

[0014] When the length of the governance space-time sequence parameters is equal to or greater than the preset space-time sequence length, the hydrological information type fusion conditions are set, and the hydrological information type fusion conditions and the governance space-time sequence parameters are input into the non-human activity hydrological fluctuation governance algorithm to obtain the geographical location terrain change type of the urban construction area.

[0015] Furthermore, the steps for establishing the algorithm for managing hydrological fluctuations caused by human activities are as follows:

[0016] According to different multivariate heterogeneous spatial data, the types of hydrological information at different altitudes in urban construction areas and the corresponding geographical location terrain change type data are sorted out;

[0017] Process and spatially convolve the hydrological information types of different seasons in the statistical area, and convert the raw data into practical features for use by the Transformer algorithm;

[0018] Using the Transformer algorithm, calculate the data according to the prepared activation function, use the selected algorithm to calculate the model activation function, and adjust the model parameters;

[0019] After the activation function calculation is completed, the relevant parameters of the model are extracted as the output of the algorithm for managing hydrological fluctuations caused by human activities.

[0020] Furthermore, the steps for establishing the algorithm for managing hydrological fluctuations caused by non-human activities are as follows:

[0021] According to different multivariate heterogeneous spatial data, the fusion conditions of hydrological information types in urban construction areas and the corresponding geographical location terrain change type data are sorted out;

[0022] The Transformer model is used for training, with the hydrological information type fusion condition as the independent variable and the geographical location terrain change type parameter as the dependent variable to reduce the data length and calculate the activation function of the model;

[0023] After the activation function is calculated, the non-human activity hydrological fluctuation management algorithm is used to predict the geographical location terrain change type parameters of the urban construction area;

[0024] Transformer is performed on different multivariate heterogeneous spatial data to calculate the correlation coefficient between the parameters of geographical location terrain change type and the actual geographical location terrain change type.

[0025] Furthermore, the data collection method of the hydrological information type fusion condition includes:

[0026] Use temperature monitoring devices to monitor and collect temperature change ranges in urban construction areas; use rainfall monitoring systems to monitor and collect rainfall in urban construction areas; monitor and collect religious beliefs in urban construction areas, and analyze peak values ​​and fluctuation ranges of temperature changes; use remote sensing systems to monitor and collect animal and plant species signals generated in urban construction areas; use the household registration management system to collect population migration speeds around urban construction areas, and count the impacts of different population migration speeds.

[0027] Furthermore, the preset influencing factors of the preset spatiotemporal sequence length include data sparsity, data acquisition noise, data error, convolution speed and parameter settings of the model.

[0028] On the other hand, the present application also provides a control unit of a data fusion management method based on multi-heterogeneous geographic information, including:

[0029] A multivariate heterogeneous spatial data acquisition unit is used to collect different multivariate heterogeneous spatial data of the urban construction area, wherein the different multivariate heterogeneous spatial data include different types of terrain change at different altitudes of different urban construction areas and hydrological information at different altitudes of the urban construction area within a preset time before the terrain change at different altitudes occurs;

[0030] The hydrological information at different altitudes in the urban construction area includes population distribution, water source distribution, temperature change range, rainfall, plant and animal species, population migration speed and religious beliefs in the urban construction area during operation; the population distribution and water source distribution are collected per unit time, and the temperature change range, rainfall, plant and animal species, population migration speed and religious beliefs are collected according to the preset urban planning;

[0031] An information fusion unit is used to receive terrain change types and hydrological information at different altitudes at different geographical locations, classify hydrological information at different altitudes in urban construction areas based on hydrological information statistics, and obtain hydrological information types and fusion conditions for hydrological information types in different seasons within the statistical area; the hydrological information types in different seasons within the statistical area include population distribution and water source distribution, and the hydrological information type fusion conditions include temperature change range, rainfall, animal and plant species, population migration speed, and religious beliefs;

[0032] Transformer algorithm unit, used to receive the types of hydrological information and fusion conditions of hydrological information types in different seasons in the statistical area and upload them to the Transformer algorithm to establish algorithms for managing hydrological fluctuations caused by human activities and those for managing hydrological fluctuations caused by non-human activities;

[0033] The input of the algorithm for managing hydrological fluctuations caused by human activities is the types of hydrological information in different seasons in the statistical area, and the output is the management spatiotemporal sequence parameters of the algorithm for managing hydrological fluctuations caused by non-human activities; the input of the algorithm for managing hydrological fluctuations caused by non-human activities is the fusion conditions of the types of hydrological information and the determined spatiotemporal sequence parameters of management, and the output is the type of terrain change in the geographical location of the urban construction area;

[0034] The control spatiotemporal sequence parameter unit is used to receive the hydrological fluctuation control algorithm for human activities and the hydrological fluctuation control algorithm for non-human activities; collect the types of hydrological information in different seasons in the statistical area per unit time, and input them into the hydrological fluctuation control algorithm for human activities to obtain the control spatiotemporal sequence parameters of the hydrological fluctuation control algorithm for non-human activities;

[0035] The geographical location terrain change analysis unit is used to receive the governance spatiotemporal sequence parameters of the non-human activity hydrological fluctuation governance algorithm, and compare the governance spatiotemporal sequence parameters of the non-human activity hydrological fluctuation governance algorithm with the preset spatiotemporal sequence length:

[0036] When the length of the governance space-time sequence parameter is less than the preset space-time sequence length, there is no need to set the fusion conditions of the hydrological information types, and the collection and analysis of the hydrological information types in different seasons in the statistical area should continue;

[0037] When the length of the governance space-time sequence parameters is equal to or greater than the preset space-time sequence length, the hydrological information type fusion conditions are set, and the hydrological information type fusion conditions and the governance space-time sequence parameters are input into the non-human activity hydrological fluctuation governance algorithm to obtain the geographical location terrain change type of the urban construction area.

[0038] Beneficial effects:

[0039] The present invention proposes a data fusion management method based on multivariate heterogeneous geographic information. By collecting these data, the method can fully understand the operating status of the urban construction area; the method uses the Transformer algorithm to establish an algorithm for managing hydrological fluctuations caused by human activities and an algorithm for managing hydrological fluctuations caused by non-human activities. By activating function calculation and model training of different multivariate heterogeneous spatial data and corresponding types of geographical location terrain changes, the model can identify and classify different types of geographical location terrain changes in urban construction areas; according to the comparison between the management spatiotemporal sequence parameters and the preset spatiotemporal sequence length, it can be determined whether it is necessary to set the fusion condition of the hydrological information type, and the geographical location terrain change type of the urban construction area can be discovered in time. By integrating a variety of hydrological information and the application of the Transformer algorithm, the adjustment accuracy of the geographical location terrain change in the urban construction area can be improved, not only the geographical location terrain change type can be judged, but also the geographical location terrain change prediction and trend analysis can be performed according to different altitude data. The method uses a variety of hydrological information and Transformer technology to realize the fusion management of the status of large urban construction areas in different seasons and the adjustment of geographical location terrain changes, ensuring seasonal safety and accurate monitoring of hydrological information per unit time in the urban construction area. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] Figure 1 is a flow chart of the method of the present invention;

[0041] Figure 2 It is a composition diagram of the method implementation unit of the present invention. DETAILED DESCRIPTION

[0042] It should be noted that, in the absence of conflict, the embodiments and features in the embodiments of the present application may be combined with each other. The present application will be further described in detail below in conjunction with the accompanying drawings and specific embodiments.

[0043] like Figure 1 As shown, a data fusion management method based on multi-heterogeneous geographic information of the present invention specifically includes the following steps:

[0044] S100, collecting different multivariate heterogeneous spatial data of urban construction areas, wherein the different multivariate heterogeneous spatial data include different types of terrain change at different altitudes of different urban construction areas and hydrological information at different altitudes of urban construction areas within a preset time before the terrain change at different altitudes occurs;

[0045] In order to achieve the integrated governance of the status of large-scale urban construction areas in different seasons, it is first necessary to collect different multivariate heterogeneous spatial data of urban construction areas. These data can provide information about the performance of urban construction areas during operation, the types of geographical location and terrain changes, and related hydrological information, providing a basis for subsequent status evaluation and geographical location and terrain change adjustments;

[0046] The hydrological information at different altitudes in the urban construction area includes:

[0047] Population distribution and water source distribution: Collect the population distribution and water source distribution of urban construction areas, and analyze the fluctuations in population distribution and water source distribution; the fluctuations in population distribution and water source distribution can reflect the stability of urban construction areas. It is necessary to collect the population distribution and water source distribution parameters of urban construction areas per unit time, and record their fluctuations.

[0048] Temperature variation range: Based on the temperature monitoring device, the temperature variation range of the urban construction area is monitored and collected, including the maximum value, average value and variance of the temperature variation range. The change of the temperature variation range can reflect the mechanical operation status and geographical location and terrain changes in the urban construction area.

[0049] Precipitation: The rainfall monitoring system is used to monitor and collect rainfall changes in urban construction areas, including rainfall inside and outside the equipment. Abnormal changes in rainfall can indicate geographical location and terrain changes such as overload and poor heat dissipation in urban construction areas.

[0050] Plant and animal species: Based on the remote sensing system, the plant and animal species signals generated in the urban construction area are monitored and collected, and analyzed. The plant and animal species signals can provide status information within the urban construction area.

[0051] Population migration speed: Based on the household registration management system, the population migration speed around the urban construction area is collected, and the impact changes caused by different population migration speeds are counted, and the abnormal changes caused by different population migration speeds are counted.

[0052] Religious beliefs: Monitor and collect religious beliefs in urban construction areas, analyze the peak and fluctuation range of temperature changes, and the test results of religious beliefs can provide information about insulation performance.

[0053] By collecting and recording these hydrological information at different altitudes, an information database of urban construction areas is established for subsequent data analysis, correlation analysis and model activation function calculation; wherein, the population distribution and water source distribution are collected per unit time, and the temperature change range, rainfall, animal and plant species, population migration speed and religious beliefs are collected according to the preset urban planning; by collecting different multivariate heterogeneous spatial data of urban construction areas, basic data on the performance of urban construction areas during operation and the types of geographical location and terrain changes can be provided, providing an important basis for subsequent status evaluation, geographical location and terrain change adjustments and performance optimization.

[0054] By analyzing different multivariate heterogeneous spatial data, we can reveal information such as the stability of urban construction areas, mechanical operating status, insulation performance, and potential geographical location and terrain changes. In addition to the fluctuating data on population distribution and water source distribution, through temperature monitoring devices, rainfall monitoring systems, animal and plant species detection, household registration management systems, and religious belief detection and other detection methods, we can conduct all-round integrated governance of urban construction areas, collect status information of urban construction areas from different angles, and improve the accuracy of detection and adjustment of geographical location and terrain changes.

[0055] By collecting different multivariate heterogeneous spatial data and hydrological information in urban construction areas, we can fully understand the performance, geographical location terrain change types and hydrological information of urban construction areas, and provide basic data and basis for subsequent status assessment, geographical location terrain change adjustment and performance optimization.

[0056] S200, classifying the hydrological information at different altitudes in the urban construction area according to the hydrological information statistics, obtaining the types of hydrological information in different seasons in the statistical area and the fusion conditions of the hydrological information types, wherein the types of hydrological information in different seasons in the statistical area include population distribution and water source distribution, and the fusion conditions of the hydrological information types include temperature change range, rainfall, plant and animal species, population migration speed and religious beliefs;

[0057] In this step, it is necessary to classify the hydrological information at different altitudes in the urban construction area according to the hydrological information statistics, and divide the hydrological information at different altitudes into two different information, namely, the types of hydrological information in different seasons in the statistical area and the fusion conditions of the hydrological information types;

[0058] The types of hydrological information in different seasons in the statistical area include population distribution and water source distribution. These data can be collected by monitoring and collecting population distribution and water source distribution parameters in the urban construction area per unit time;

[0059] The fusion conditions of hydrological information types include temperature change range, rainfall, animal and plant species, population migration speed and religious beliefs, which are used to monitor and collect the status of temperature change range, rainfall, animal and plant species, population migration speed and religious beliefs in the operation process of urban construction areas;

[0060] The classification basis of hydrological information types and fusion conditions of hydrological information types in different seasons in the statistical area is as follows:

[0061] Different types of geographical location terrain changes correspond to different hydrological information. By classifying population distribution and water source distribution separately from other multiple feature data, different types of geographical location terrain changes can be judged and analyzed more specifically. Population distribution and water source distribution fluctuations are more likely to be related to geographical location terrain changes in different seasons, while temperature change ranges, rainfall, sound and other data are more likely to be related to mechanical or insulating geographical location terrain changes. Population distribution and water source distribution are more convenient to collect in unit time fusion management. These data can be used to quickly make preliminary judgments on geographical location terrain changes.

[0062] The fusion conditions of hydrological information types involve more sensor collection and detection equipment, which requires a certain amount of time and cost. Therefore, by presetting a preset spatiotemporal sequence length, if the governance spatiotemporal sequence parameters of hydrological information types in different seasons in the statistical area are less than the preset spatiotemporal sequence length, it is possible to avoid frequently setting the fusion conditions of hydrological information types, thereby improving the governance effect.

[0063] By dividing the hydrological information into two types of information, it is possible to more specifically judge and analyze different types of geographical location terrain changes; by presetting a preset space-time sequence length, if the governance space-time sequence parameters of different seasons of hydrological information types in the statistical area are less than the preset space-time sequence length, it is possible to avoid frequently setting the fusion conditions of the hydrological information types, thereby improving the governance effect; by classifying different types of hydrological information separately, more accurate judgment and adjustment results can be obtained by comprehensively analyzing the correlation between different feature data.

[0064] S300, uploading the types of hydrological information in different seasons in the statistical area, the conditions for the fusion of hydrological information types, and the types of terrain changes at different altitudes in the corresponding urban construction area to the Transformer algorithm, and establishing an algorithm for managing hydrological fluctuations caused by human activities and an algorithm for managing hydrological fluctuations caused by non-human activities;

[0065] The steps to establish the algorithm for managing hydrological fluctuations caused by human activities are as follows:

[0066] According to the different multivariate heterogeneous spatial data of the urban construction area collected in step S100, sorting out the different types of hydrological information at different altitudes of the urban construction area and the corresponding geographical location terrain change type data;

[0067] Process and spatially convolve the hydrological information types of different seasons in the statistical area, and convert the raw data into practical features for use by the Transformer algorithm;

[0068] According to the problem description, select the Transformer algorithm suitable for the scenario, use the selected algorithm to calculate the model activation function, and adjust the model parameters;

[0069] After the activation function calculation is completed, the relevant parameters of the model are extracted as the output of the algorithm for managing hydrological fluctuations caused by human activities.

[0070] The steps to establish the algorithm for managing hydrological fluctuations caused by non-human activities are as follows:

[0071] According to the different multivariate heterogeneous spatial data of the urban construction area collected in step S100, the fusion conditions of the hydrological information types of the urban construction area and the corresponding geographical location terrain change type data are sorted out;

[0072] The Transformer model is used for training, with the hydrological information type fusion condition as the independent variable and the geographical location terrain change type parameter as the dependent variable to reduce the data length and calculate the activation function of the model;

[0073] After the activation function is calculated, the non-human activity hydrological fluctuation management algorithm is used to predict the geographical location and terrain change type of the urban construction area.

[0074] The non-human activity hydrological fluctuation management algorithm is trained using the Transformer model, and the expression is:

[0075]

[0076] Among them, R s is the output of the Transformer model activation function, Q is the feature spatiotemporal sequence, X represents the number of convolutional layers, V is the activation function coefficient, and Z d is the Transformer model signal, W x W represents the error coefficient of the temperature change range for judging the type of terrain change in geographical location, y W represents the error coefficient of rainfall on the type of terrain change in geographical location. z W represents the error coefficient of the judgment of plant and animal species on the type of terrain change in geographical location, i The error coefficient of population migration speed on the type of terrain change in geographical location, W j It represents the error coefficient of the effect of religious belief on the judgment of the type of terrain change in geographical location, ⊙ is the Hadamard product operator, and * is the convolution operator.

[0077] The expression of the algorithm for controlling hydrological fluctuations due to non-human activities is:

[0078]

[0079] Among them, F u The parameters representing the geographical location and terrain change type of the urban construction area, L, D, and J are the learnable spatiotemporal sequences obtained by transforming the project embedding spatiotemporal sequence, corresponding to query, key, and value, respectively, and K o is the learnable spatiotemporal sequence of the output positions of the multi-head self-attention, Add(addition) is the output addition, output(N r ) is the hydrological fluctuation caused by non-human activities, ReLU represents the activation function, Attention represents the self-attention mechanism, a, b, c, d, and e represent the temperature change range, rainfall, plant and animal species, population migration speed, and religious beliefs, respectively.

[0080] Establish a corresponding relationship between the geographical location terrain change type parameter Y and the actual geographical location terrain change type; specifically, by performing activation function calculation and model training on different multivariate heterogeneous spatial data, the corresponding relationship between the geographical location terrain change type parameter Y and the actual geographical location terrain change type is obtained, and by performing Transformer algorithms such as classification and regression on different multivariate heterogeneous spatial data, the correlation coefficient between the geographical location terrain change type parameter Y and the actual geographical location terrain change type is calculated;

[0081] The input of the algorithm for managing hydrological fluctuations caused by human activities is the types of hydrological information in different seasons in the statistical area, and the output is the management spatiotemporal sequence parameters of the algorithm for managing hydrological fluctuations caused by non-human activities; the input of the algorithm for managing hydrological fluctuations caused by non-human activities is the fusion conditions of the types of hydrological information and the determined spatiotemporal sequence parameters of management, and the output is the type of terrain change in the geographical location of the urban construction area;

[0082] This step can obtain complete input information by sorting and processing the types of hydrological information and geographical location terrain change types at different altitudes in the urban construction area, so that the hydrological fluctuation management algorithm can more accurately judge the status of the equipment and the type of geographical location terrain change; use the prepared activation function calculation data to calculate the model activation function of the selected Transformer algorithm, and adjust the model parameters, which can improve the accuracy and performance of the model by continuously optimizing the model parameters and algorithm selection; by outputting the management spatiotemporal sequence parameters, it can understand the importance of each feature to the judgment of the geographical location terrain change type, so as to better understand the relationship between hydrological fluctuations and geographical location terrain change types;

[0083] In summary, the hydrological fluctuation management algorithm can more accurately evaluate the status of urban construction areas and the type of geographical location terrain changes, providing effective decision support and guidance for eliminating geographical location terrain changes for brake personnel.

[0084] S400, collecting the types of hydrological information in different seasons in the statistical area of ​​the urban construction area per unit time, and inputting them into the algorithm for managing hydrological fluctuations caused by human activities, so as to obtain the management spatiotemporal sequence parameters of the algorithm for managing hydrological fluctuations caused by non-human activities;

[0085] In this step, data is preprocessed before input, including data desensitization, sorting, and normalization, to ensure the quality and consistency of data input into the model;

[0086] The types of hydrological information collected in different seasons in the statistical area per unit time are used as input and passed to the artificial activity hydrological fluctuation management algorithm for spatiotemporal convolution and state evaluation, providing management spatiotemporal sequence parameters for the subsequent non-artificial activity hydrological fluctuation management algorithm; the management spatiotemporal sequence parameters reflect the current state and performance status of the urban construction area. Through the management spatiotemporal sequence parameters, the operation status of the urban construction area can be preliminarily judged and evaluated;

[0087] In this step, through preprocessing steps such as data desensitization, sorting and normalization, the quality and consistency of the data input into the model can be ensured, outliers, noise and inconsistent sampling rates in the data can be eliminated, and the accuracy and reliability of the monitoring algorithm can be improved;

[0088] The governance spatiotemporal sequence parameters obtained through the algorithm for managing hydrological fluctuations caused by human activities can reflect the current state and performance of urban construction areas. These governance spatiotemporal sequence parameters can be used for preliminary judgment and evaluation of urban construction areas, and provide important input for subsequent algorithms for managing hydrological fluctuations caused by non-human activities.

[0089] By continuously integrating governance and evaluating the status of urban construction areas, potential geographical location and terrain changes or abnormal conditions can be discovered in a timely manner, so that maintenance measures can be taken in advance to avoid the impact of equipment geographical location and terrain changes on supply in different seasons. By analyzing and evaluating the status of urban construction areas per unit time, equipment operation strategies can be optimized and the operating efficiency and energy utilization efficiency of urban construction areas can be improved.

[0090] S500, comparing the governance spatiotemporal sequence parameters of the non-human activity hydrological fluctuation governance algorithm with the preset spatiotemporal sequence length:

[0091] When the length of the governance space-time sequence parameter is less than the preset space-time sequence length, there is no need to set the fusion conditions of the hydrological information types, and the collection and analysis of the hydrological information types in different seasons in the statistical area should continue;

[0092] When the length of the governance space-time sequence parameters is equal to or greater than the preset space-time sequence length, the hydrological information type fusion conditions are set, and the hydrological information type fusion conditions and the governance space-time sequence parameters are input into the non-human activity hydrological fluctuation governance algorithm to obtain the geographical location terrain change type of the urban construction area.

[0093] The preset spatiotemporal sequence length refers to a fixed value or range used to determine whether it is necessary to set the fusion conditions of hydrological information types. The preset spatiotemporal sequence length is preset based on the following factors: data sparsity, data acquisition noise, data error and convolution speed, and model parameter settings.

[0094] Furthermore, the preset length of space-time sequences is a dynamic process, which needs to be adjusted and optimized according to actual conditions. By continuously observing and analyzing the system operation status, geographic location and terrain change data, and maintenance records, it is necessary to continuously optimize the preset length of space-time sequences to improve the accuracy and reliability of state fusion management.

[0095] When the length of the governance spatiotemporal sequence parameter is less than the preset spatiotemporal sequence length, the evaluation result of the human activity status representing the urban construction area shows that it is in a normal state. In this case, there is no need to set the fusion conditions of the hydrological information types, and the collection and analysis of the initial hydrological information types can continue to be maintained to help monitor and collect the basic operating status of the urban construction area;

[0096] If the governance spatiotemporal sequence parameter is equal to or greater than the preset spatiotemporal sequence length, it means that the human activity status assessment result of the urban construction area indicates the existence of potential geographical location terrain changes or abnormal conditions. In this case, it is necessary to set the hydrological information type fusion condition and input it into the non-human activity hydrological fluctuation governance algorithm together with the human activity governance spatiotemporal sequence parameter to obtain the geographical location terrain change type of the urban construction area;

[0097] The algorithm for managing hydrological fluctuations caused by non-human activities will comprehensively consider the types of hydrological information in different seasons in the statistical area, the conditions for the fusion of hydrological information types, and the preset spatial and temporal sequence parameters for management, and use algorithms such as Transformer to calculate and analyze activation functions, so as to determine the type of geographical location and terrain changes in the urban construction area;

[0098] By comparing the governance spatiotemporal sequence parameters with the preset spatiotemporal sequence length, it is possible to quickly determine whether the urban construction area is in a normal state, thereby deciding whether it is necessary to set the fusion conditions of hydrological information types. If the governance spatiotemporal sequence parameters are less than the preset spatiotemporal sequence length, additional data collection and analysis can be avoided, saving time and resources.

[0099] When the governance space-time sequence parameter is equal to or greater than the preset space-time sequence length, the hydrological information type fusion condition is set, and it is input into the non-human activity hydrological fluctuation governance algorithm together with the governance space-time sequence parameter, which can provide accurate judgment of the type of geographical location terrain change. By comprehensively considering multiple data information and preset parameters, using algorithms such as Transformer to calculate and analyze the activation function, the geographical location terrain change type of the urban construction area can be accurately determined;

[0100] The determination of the preset space-time sequence length is based on multiple factors. By comprehensively considering these factors, a preset space-time sequence length suitable for specific urban construction areas is formulated to improve the accuracy and reliability of state fusion management. By observing and analyzing the system operating status, geographical location and terrain change data, and maintenance records, the preset space-time sequence length can be continuously optimized to adapt to the actual operating conditions of urban construction areas and improve the accuracy and reliability of the monitoring algorithm.

[0101] like Figure 2 As shown, a data fusion management method based on multi-heterogeneous geographic information of the present invention is implemented through different control units, including:

[0102] A multivariate heterogeneous spatial data acquisition unit is used to collect different multivariate heterogeneous spatial data of the urban construction area, wherein the different multivariate heterogeneous spatial data include different types of terrain change at different altitudes of different urban construction areas and hydrological information at different altitudes of the urban construction area within a preset time before the terrain change at different altitudes occurs;

[0103] The hydrological information at different altitudes in the urban construction area includes population distribution, water source distribution, temperature change range, rainfall, plant and animal species, population migration speed and religious beliefs in the urban construction area during operation; the population distribution and water source distribution are collected per unit time, and the temperature change range, rainfall, plant and animal species, population migration speed and religious beliefs are collected according to the preset urban planning;

[0104] An information fusion unit is used to receive terrain change types and hydrological information at different altitudes at different geographical locations, classify hydrological information at different altitudes in urban construction areas based on hydrological information statistics, and obtain hydrological information types and fusion conditions for hydrological information types in different seasons within the statistical area; the hydrological information types in different seasons within the statistical area include population distribution and water source distribution, and the hydrological information type fusion conditions include temperature change range, rainfall, animal and plant species, population migration speed, and religious beliefs;

[0105] Transformer algorithm unit, used to receive the types of hydrological information and fusion conditions of hydrological information types in different seasons in the statistical area and upload them to the Transformer algorithm to establish algorithms for managing hydrological fluctuations caused by human activities and those for managing hydrological fluctuations caused by non-human activities;

[0106] The input of the algorithm for managing hydrological fluctuations caused by human activities is the types of hydrological information in different seasons in the statistical area, and the output is the management spatiotemporal sequence parameters of the algorithm for managing hydrological fluctuations caused by non-human activities; the input of the algorithm for managing hydrological fluctuations caused by non-human activities is the fusion conditions of the types of hydrological information and the determined spatiotemporal sequence parameters of management, and the output is the type of terrain change in the geographical location of the urban construction area;

[0107] The control spatiotemporal sequence parameter unit is used to receive the hydrological fluctuation control algorithm for human activities and the hydrological fluctuation control algorithm for non-human activities; collect the types of hydrological information in different seasons in the statistical area per unit time, and input them into the hydrological fluctuation control algorithm for human activities to obtain the control spatiotemporal sequence parameters of the hydrological fluctuation control algorithm for non-human activities;

[0108] The geographical location terrain change analysis unit is used to receive the governance spatiotemporal sequence parameters of the non-human activity hydrological fluctuation governance algorithm, and compare the governance spatiotemporal sequence parameters of the non-human activity hydrological fluctuation governance algorithm with the preset spatiotemporal sequence length:

[0109] When the length of the governance space-time sequence parameter is less than the preset space-time sequence length, there is no need to set the fusion conditions of the hydrological information types, and the collection and analysis of the hydrological information types in different seasons in the statistical area should continue;

[0110] When the length of the governance space-time sequence parameters is equal to or greater than the preset space-time sequence length, the hydrological information type fusion conditions are set, and the hydrological information type fusion conditions and the governance space-time sequence parameters are input into the non-human activity hydrological fluctuation governance algorithm to obtain the geographical location terrain change type of the urban construction area.

[0111] The system collects terrain change types and hydrological information at different altitudes in urban construction areas, and performs information fusion and Transformer algorithm to achieve comprehensive integrated governance of the status of urban construction areas. Compared with the traditional method of only integrating and managing population distribution and water source distribution parameters, the system considers more hydrological information and provides a more comprehensive and comprehensive status assessment.

[0112] The system uses a combination of anthropogenic hydrological fluctuation management algorithms and non-human induced hydrological fluctuation management algorithms to evaluate the status of urban construction areas. The anthropogenic hydrological fluctuation management algorithm collects and counts hydrological information of different seasons in the area per unit time, which is more time-efficient and rapid; while the non-human induced hydrological fluctuation management algorithm comprehensively considers the types of terrain changes at different altitudes and hydrological information at different altitudes, which is more accurate and reliable.

[0113] By comparing the governance spatiotemporal sequence parameters of the non-human activity hydrological fluctuation governance algorithm with the preset spatiotemporal sequence length, the geographical location terrain change type of the urban construction area can be determined. Since the system comprehensively considers the geographical location terrain change type at different altitudes and the hydrological information at different altitudes, and uses a hierarchical evaluation method, it can improve the accuracy of the judgment of the geographical location terrain change type and reduce the possibility of misjudgment and missed judgment.

[0114] In summary, this method uses a variety of hydrological information and Transformer technology to achieve the integrated management of the status of large urban construction areas in different seasons and the adjustment of geographical location and terrain changes, ensuring seasonal safety and accurate monitoring of hydrological information per unit time in urban construction areas.

[0115] The various variations and specific embodiments of the state fusion governance method for large-scale urban construction areas with different seasons in the aforementioned embodiment 1 are also applicable to the state fusion governance system for large-scale urban construction areas with different seasons in this embodiment. Through the aforementioned detailed description of the state fusion governance method for large-scale urban construction areas with different seasons, those skilled in the art can clearly know the implementation method of the state fusion governance system for large-scale urban construction areas with different seasons in this embodiment, so for the sake of brevity of the specification, it will not be described in detail here.

[0116] Although embodiments of the present invention have been shown and described, it will be understood by those skilled in the art that various equivalent changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A data fusion management method based on multi-heterogeneous geographic information, characterized in that: The method comprises: S100, collecting different multivariate heterogeneous spatial data of urban construction areas, wherein the different multivariate heterogeneous spatial data include different types of terrain change at different altitudes of different urban construction areas and hydrological information at different altitudes of urban construction areas within a preset time before the terrain change at different altitudes occurs; S200, classifying the hydrological information at different altitudes in the urban construction area according to the hydrological information statistics, and obtaining the types of hydrological information in different seasons in the statistical area and the conditions for merging the types of hydrological information; S300, uploading the types of hydrological information in different seasons in the statistical area, the conditions for the fusion of hydrological information types, and the types of terrain changes at different altitudes in the corresponding urban construction area to the Transformer algorithm, and establishing an algorithm for managing hydrological fluctuations caused by human activities and an algorithm for managing hydrological fluctuations caused by non-human activities; S400, collecting the types of hydrological information in different seasons in the statistical area of ​​the urban construction area per unit time, and inputting them into the algorithm for managing hydrological fluctuations caused by human activities, so as to obtain the management spatiotemporal sequence parameters of the algorithm for managing hydrological fluctuations caused by non-human activities; S500, comparing the governance spatiotemporal sequence parameters of the non-human activity hydrological fluctuation governance algorithm with the preset spatiotemporal sequence length: when the governance spatiotemporal sequence parameter length is less than the preset spatiotemporal sequence length, there is no need to set the hydrological information type fusion condition, and continue to maintain the collection and analysis of hydrological information types in different seasons in the statistical area; when the governance spatiotemporal sequence parameter length is equal to or greater than the preset spatiotemporal sequence length, set the hydrological information type fusion condition, and input the hydrological information type fusion condition and the governance spatiotemporal sequence parameter into the non-human activity hydrological fluctuation governance algorithm to obtain the geographical location terrain change type of the urban construction area; The hydrological information at different altitudes in the urban construction area includes population distribution, water source distribution, temperature change range, rainfall, animal and plant species, population migration speed and religious beliefs in the urban construction area during operation; the population distribution and water source distribution are collected per unit time, and the temperature change range, rainfall, animal and plant species, population migration speed and religious beliefs are collected according to the preset urban planning; The types of hydrological information in different seasons in the statistical area include population distribution and water source distribution, and the fusion conditions of the hydrological information types include temperature change range, rainfall, animal and plant species, population migration speed and religious beliefs; The input of the non-human activity hydrological fluctuation management algorithm is the fusion conditions of the hydrological information types and the determined management time and space sequence parameters, and the output is the geographical location terrain change type of the urban construction area; The steps for establishing the algorithm for managing hydrological fluctuations caused by human activities are as follows: According to different multivariate heterogeneous spatial data, the types of hydrological information at different altitudes in the urban construction area and the corresponding geographical location terrain change type data are sorted out; the types of hydrological information in different seasons in the statistical area are processed and time-space convolved to convert the original data into practical features for use by the Transformer algorithm; Using the Transformer algorithm, according to the prepared activation function calculation data, the selected algorithm is used to calculate the model activation function, and the model parameters are adjusted; after the activation function calculation is completed, the relevant parameters of the model are extracted as the output of the algorithm for managing hydrological fluctuations caused by human activities; The steps for establishing the algorithm for managing hydrological fluctuations caused by non-human activities are as follows: According to different multivariate heterogeneous spatial data, the fusion conditions of hydrological information types in urban construction areas and the corresponding geographical location terrain change type data are sorted out; The Transformer model is used for training, with the hydrological information type fusion condition as the independent variable and the geographical location terrain change type parameter as the dependent variable to reduce the data length and calculate the activation function of the model; After the activation function is calculated, the non-human activity hydrological fluctuation management algorithm is used to predict the geographical location terrain change type parameters of the urban construction area, and the Transformer is performed on different multivariate heterogeneous spatial data to calculate the correlation coefficient between the geographical location terrain change type parameters and the actual geographical location terrain change type; The data collection method for the fusion conditions of the hydrological information types includes: using a temperature monitoring device to monitor and collect the temperature change interval of the urban construction area; monitoring and collecting the rainfall in the urban construction area based on a rainfall monitoring system; monitoring and collecting the religious beliefs in the urban construction area, and analyzing the peak value and fluctuation range of temperature changes; using a remote sensing system to monitor and collect the animal and plant species signals generated in the urban construction area; using a household registration management system to collect the population migration speed around the urban construction area, and statistically analyzing the impact of different population migration speeds; The preset factors affecting the preset spatiotemporal sequence length include data sparsity, data acquisition noise, data error, convolution speed and parameter settings of the model.

2. A data fusion management method based on multi-heterogeneous geographic information as claimed in claim 1, characterized in that: The method is implemented through different control units, including: A multivariate heterogeneous spatial data acquisition unit is used to collect different multivariate heterogeneous spatial data of the urban construction area, wherein the different multivariate heterogeneous spatial data include different types of terrain change at different altitudes of different urban construction areas and hydrological information at different altitudes of the urban construction area within a preset time before the terrain change at different altitudes occurs; An information fusion unit is used to receive terrain change types and hydrological information at different altitudes at different geographical locations, classify hydrological information at different altitudes in urban construction areas based on hydrological information statistics, and obtain hydrological information types and fusion conditions for hydrological information types in different seasons within the statistical area; the hydrological information types in different seasons within the statistical area include population distribution and water source distribution, and the hydrological information type fusion conditions include temperature change range, rainfall, animal and plant species, population migration speed, and religious beliefs; The Transformer algorithm unit is used to receive the types of hydrological information in different seasons in the statistical area and the fusion conditions of the hydrological information types and upload them to the Transformer algorithm to establish an algorithm for managing hydrological fluctuations caused by human activities and an algorithm for managing hydrological fluctuations caused by non-human activities; wherein the input of the algorithm for managing hydrological fluctuations caused by human activities is the types of hydrological information in different seasons in the statistical area, and the output is the management spatiotemporal sequence parameters of the algorithm for managing hydrological fluctuations caused by non-human activities; the input of the algorithm for managing hydrological fluctuations caused by non-human activities is the fusion conditions of the types of hydrological information and the determined management spatiotemporal sequence parameters, and the output is the type of geographical location and terrain changes in the urban construction area; The control spatiotemporal sequence parameter unit is used to receive the hydrological fluctuation control algorithm for human activities and the hydrological fluctuation control algorithm for non-human activities; collect the types of hydrological information in different seasons in the statistical area per unit time, and input them into the hydrological fluctuation control algorithm for human activities to obtain the control spatiotemporal sequence parameters of the hydrological fluctuation control algorithm for non-human activities; The geographical location terrain change analysis unit is used to receive the governance space-time sequence parameters of the non-human activity hydrological fluctuation governance algorithm, and compare the governance space-time sequence parameters of the non-human activity hydrological fluctuation governance algorithm with the preset space-time sequence length.

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