Planning index distribution optimization method and system in stock planning environment

Abstract

The invention provides a planning index distribution optimization method and system in a stock planning environment, and relates to the technical field of space planning, and the method comprises the steps: building a digital twin platform, carrying out the multi-protection ownership confirmation, carrying out the three-dimensional value evaluation of space resources through an evaluation network, and building an evaluation result; performing resource configuration according to the evaluation result and the multi-protection ownership confirmation result; carrying out space resource flow processing by utilizing a resource configuration result, and carrying out ownership adjustment according to a multi-protection ownership confirmation result; a flow monitoring result and a resource configuration result of space resource flow processing are compared, and a space resource damage identifier is established; and executing balance optimization under the space resource damage identification to complete planning index distribution optimization. The technical problem of unreasonable space resource allocation caused by lack of dynamic monitoring and multi-dimensional value evaluation in the prior art is solved, the rationality of resource allocation is improved, and the adaptability and scientificity of planning index allocation are enhanced.

Description

Technical Field

[0001] The present application relates to the field of spatial planning technology, and specifically to a planning indicator allocation optimization method and system in a stock planning environment. Background Art

[0002] The allocation of planning indicators is an important part of spatial resource management, which determines the rational allocation and effective use of resources such as land, buildings, and infrastructure. In the stock planning environment, the allocation of spatial resources no longer depends on large-scale new development, but is based on the optimal allocation of existing resources.

[0003] The allocation of planning indicators in the existing stock planning environment mainly relies on static functional zoning and use control, and forms the supply and demand relationship of resource elements through a combination of administrative means and market mechanisms. For example, resource flow is guided by setting use limits or formulating use control measures. These methods can meet the basic resource allocation needs to a certain extent, but they have many limitations. First, the existing methods lack dynamic monitoring and real-time data support for spatial resources, and it is difficult to adapt to the complex and changeable resource needs in stock planning. Secondly, traditional methods are mostly static blueprint planning in resource allocation, which lacks flexibility, making it easy for resources to be mismatched, inefficiently circulated, and even wasted in the process of market circulation and adjustment. In addition, the existing methods are relatively single in the value assessment of spatial resources, and fail to fully consider the ownership relationship and multi-dimensional value, resulting in inefficient resource allocation and difficulty in achieving optimal utilization of resources and scientific implementation of planning. Summary of the invention

[0004] This application provides a method and system for optimizing the allocation of planning indicators in a stock planning environment, which solves the technical problems of the prior art, such as the lack of dynamic monitoring and multi-dimensional value assessment, which leads to unreasonable allocation of spatial resources and difficulty in adapting to the dynamic changes of stock planning. It achieves the technical effect of improving the rationality of resource allocation and enhancing the adaptability and scientificity of planning indicator allocation.

[0005] In view of the above problems, on the one hand, the present application provides a planning indicator allocation optimization method in a stock planning environment, the method comprising: building a digital twin platform for space resources, the digital twin platform for space resources being constructed through drone aerial survey collection and data interaction; using the digital twin platform for space resources to perform multi-dimensional ownership confirmation, and using an evaluation network to perform a three-dimensional value evaluation of space resources, and establishing an evaluation result; performing resource allocation based on the evaluation result and the multi-dimensional ownership confirmation result, and establishing a resource allocation result, wherein the resource allocation includes a rigid configuration and a flexible configuration; using the resource allocation result to perform space resource flow processing in the tertiary market, and adjusting the ownership based on the multi-dimensional ownership confirmation result; establishing flow monitoring for space resource flow processing, establishing flow monitoring results, using a loss identification channel to compare the flow monitoring results and the resource allocation results, and establishing a space resource damage identification; configuring a balanced fitness function, executing balanced optimization under the space resource damage identification, and completing the planning indicator allocation optimization based on the balanced optimization results and the flow monitoring results.

[0006] On the other hand, the present application also provides a planning indicator allocation optimization system in a stock planning environment, and the system includes: a twin platform module, which is used to build a digital twin platform for space resources, and the digital twin platform for space resources is constructed through drone aerial survey collection and data interaction; a three-dimensional value assessment module, which is used to use the digital twin platform for space resources to perform multi-dimensional ownership confirmation, and use the assessment network to perform three-dimensional value assessment of space resources, and establish an assessment result; a resource allocation module, which is used to perform resource allocation according to the assessment result and the multi-dimensional ownership confirmation result, and establish a resource allocation result, and the resource allocation includes rigid configuration and elastic configuration; an ownership adjustment module, which is used to use the resource allocation result to process the flow of space resources in the tertiary market, and adjust the ownership according to the multi-dimensional ownership confirmation result; a flow monitoring module, which is used to establish flow monitoring of space resource flow processing, establish flow monitoring results, use the loss identification channel to compare the flow monitoring results and the resource allocation results, and establish a space resource damage identification; a balance optimization module, which is used to configure a balance fitness function, execute balance optimization under the space resource damage identification, and complete the planning indicator allocation optimization according to the balance optimization results and the flow monitoring results.

[0007] One or more technical solutions provided in this application have at least the following technical effects or advantages: Through drone aerial survey collection and data interaction, a digital twin platform for space resources is built to achieve accurate modeling of space resources and form high-precision three-dimensional spatial data, providing data support for subsequent evaluation, configuration and optimization. Through multi-dimensional ownership confirmation and three-dimensional value assessment, resource ownership is accurately identified and the multi-dimensional value of space resources is evaluated, forming a resource evaluation result with clear ownership and value, providing a decision-making basis for subsequent configuration and optimization. According to the evaluation results, resources are allocated, and the combination of rigid and flexible allocation ensures that resource allocation not only meets the rigid requirements of planning, but also has a certain degree of flexibility to adapt to the needs of dynamic changes, thereby improving the adaptability of resource allocation. Through the spatial resource flow processing and ownership adjustment in the three-level market, reasonable resource circulation is achieved, and adjustments are made in combination with ownership confirmation to improve market regulation capabilities and reduce idle or mismatched resources. By establishing flow monitoring for spatial resource flow processing, combining loss identification channels to compare flow monitoring results with resource allocation results, possible resource losses or mismatches can be accurately identified to ensure that spatial resources remain reasonable during the flow process and avoid unnecessary losses caused by transactions or adjustments. Based on the identification of damaged resources, balanced optimization is performed under the identification of damaged spatial resources. The overall balance of resource allocation is improved through optimization algorithms, the global optimization of planning indicators is achieved, and the scientific nature of planning indicator allocation is improved.

[0008] To summarize, this application acquires accurate data by building a digital twin platform, combines multi-dimensional ownership confirmation and three-dimensional value assessment to make reasonable resource allocation, considers resource flow and ownership adjustment under market factors, and establishes a monitoring and balancing optimization mechanism. It realizes the reasonable allocation of spatial resources and the optimal allocation of planning indicators under the stock planning environment, thereby significantly improving the efficiency of spatial resource utilization, enhancing the adaptability and scientific nature of planning indicator allocation, and providing new ideas and methods for urban space management under the stock planning environment.

[0009] The above description is only an overview of the technical solution of the present application. In order to more clearly understand the technical means of the present application, it can be implemented in accordance with the contents of the specification. In order to make the above and other purposes, features and advantages of the present application more obvious and easy to understand, the specific implementation methods of the present application are listed below. BRIEF DESCRIPTION OF THE DRAWINGS

[0010] Figure 1 A flowchart of a planning indicator allocation optimization method in a stock planning environment provided in an embodiment of the present application.

[0011] Figure 2 A schematic diagram of a process for establishing a spatial resource damage identification in a planning indicator allocation optimization method in a stock planning environment provided in an embodiment of the present application.

[0012] Figure 3A schematic diagram of the structure of a planning indicator allocation optimization system in a stock planning environment provided in an embodiment of the present application.

[0013] Explanation of the accompanying drawings: twin platform module 10, three-dimensional value assessment module 20, resource allocation module 30, ownership adjustment module 40, flow monitoring module 50, balance optimization module 60. DETAILED DESCRIPTION

[0014] The embodiments of the present application provide a planning indicator allocation optimization method and system in a stock planning environment, thereby solving the technical problems in the prior art that the spatial resource allocation is unreasonable and difficult to adapt to the dynamic changes of stock planning due to the lack of dynamic monitoring and multi-dimensional value evaluation, thereby achieving the technical effect of improving the rationality of resource allocation and enhancing the adaptability and scientificity of planning indicator allocation.

[0015] Embodiment 1, as Figure 1 As shown, the embodiment of the present application provides a planning indicator allocation optimization method in a stock planning environment, and the method includes: Step S1: Build a space resource digital twin platform, which is constructed through drone aerial survey collection and data interaction.

[0016] Specifically, first use a drone to take aerial photos of the target area. The drone flies according to the predetermined route and obtains information such as the terrain, landforms, and surface cover of the space resources through the equipment it carries. Then, these data are interactively integrated with other related data (such as existing land planning data, building distribution data, etc.) and imported into the digital twin platform to build a virtual space model and obtain the digital twin platform of space resources. Through the network interface, the digital twin platform of space resources is connected to external data sources such as urban databases and sensor networks to achieve real-time data updates and interactions. The constructed digital twin platform of space resources can reflect the properties and status of the physical space in real time, and support data analysis and simulation, providing an accurate and rich data foundation for subsequent multi-dimensional ownership confirmation, value assessment and other operations.

[0017] Step S2: Use the spatial resource digital twin platform to perform multi-dimensional ownership confirmation, and use the evaluation network to perform three-dimensional value evaluation of spatial resources to establish evaluation results.

[0018] Specifically, there may be multiple ownership relationships for spatial resources, such as ownership, use rights, and management rights of land. The data in the spatial resource digital twin platform constructed in step S1 are used to comprehensively and accurately define these different ownership relationships. For example, the different ownership situations of a piece of land are determined based on data such as land registration information and lease contracts. Then, using the evaluation network, the spatial resources are evaluated from three dimensions: economic value (such as land price and development potential), social value (such as public service facilities and population density), and ecological value (such as green space area and ecological sensitivity). The evaluation results that include economic, ecological, and social values ​​are established, and the evaluation results are stored in the digital twin platform to form a multi-dimensional value evaluation database. This evaluation network is an algorithm or model used for evaluation, which can be built based on technologies such as machine learning and multi-criteria decision-making.

[0019] Through multi-dimensional ownership confirmation, the ownership relationship of spatial resources is comprehensively and accurately determined, ensuring the clarity of the ownership of spatial resources. Through three-dimensional value assessment, a comprehensive scientific basis is provided for resource allocation, making planning more scientific and reasonable.

[0020] Step S3: Perform resource allocation according to the evaluation results and the multi-dimensional ownership confirmation results, and establish resource allocation results. The resource allocation includes rigid allocation and flexible allocation.

[0021] Specifically, according to the evaluation results and multi-dimensional ownership confirmation results obtained in step S2, resources are allocated according to pre-set rules, including rigid allocation and flexible allocation. For the rigid allocation part, the amount of resources that must be allocated is determined according to urban planning standards, such as land for public service facilities. In addition, the ecological value protection and social equity needs of spatial resources are also taken into account. For example, in order to protect the ecological value of a certain area, a certain area of ​​ecological protection area land will be rigidly allocated. For the flexible allocation part, market demand, development potential and other factors are comprehensively considered, and resources are allocated with reference to the market trend of economic value and the dynamic changes of social needs. For example, according to the local economic development trend and the demand for different types of housing, the proportion of residential land and commercial land is flexibly adjusted. The resource allocation process can be completed using resource allocation planning software.

[0022] By combining rigid configuration with flexible configuration, reasonable resource allocation is achieved, which not only ensures the fixed configuration of necessary resources, but also allows flexible adjustment of some resources according to actual conditions, thus improving the rationality and adaptability of resource allocation.

[0023] Step S4: Use the resource allocation results to process the spatial resource flow in the tertiary market, and adjust the ownership according to the multi-dimensional ownership confirmation results.

[0024] Specifically, in the land and other spatial resource markets, the primary market is the market where land owners transfer land use rights; the secondary market is the market where land users transfer land use rights; and the tertiary market is the market where land users re-transfer, rent, mortgage, etc. the land use rights. Using the resource allocation results obtained in step S3, simulate the flow of spatial resources in the tertiary market on the digital twin platform and analyze the market supply and demand relationship. According to the resource allocation results and market flow, adjust the ownership of spatial resources (such as the ownership and scope of the use rights) to ensure the rationality of resource allocation.

[0025] Through the resource flow processing and ownership adjustment in the tertiary market, resource allocation is optimized, resource utilization efficiency is improved, and planning is made more adaptable to market demand.

[0026] Step S5: Establish flow monitoring of space resource flow processing, establish flow monitoring results, use the loss identification channel to compare the flow monitoring results and the resource allocation results, and establish a space resource damage identification.

[0027] Specifically, intelligent terminals and edge computing nodes are deployed on the digital twin platform, and a flow monitoring system for space resource flow processing is established to monitor the flow of space resources in real time. The system can obtain relevant information on the flow of space resources by collecting market transaction data and field surveys. For example, for economic value, the price fluctuations of land or real estate in the market, changes in rental income, etc. are monitored; for ecological value, the changes in ecological and environmental indicators of space resources during use are monitored, such as changes in forest coverage and water pollution indicators; for social value, the public's satisfaction with space resources and frequency of use are monitored. Then, the loss identification channel is used to comprehensively compare the flow monitoring results with the resource allocation results from the perspectives of economic, ecological, and social values, identify and quantify damaged space resources, and establish a damaged space resource identification to provide a basis for subsequent optimization. For example, during the renovation of a community, it was found that some historical buildings were demolished. The loss identification channel was used to identify the damage to social value, and a damaged space resource identification was established to adjust resource allocation. Among them, the loss identification channel is an algorithm model used to identify whether space resources have suffered losses (such as value loss, function loss, etc.) during the flow process.

[0028] By monitoring the flow and establishing damaged space resource identification, it is possible to promptly discover damage to space resources during the flow process, provide a basis for subsequent adjustments, and help ensure the effective use and value maintenance of space resources.

[0029] Step S6: configure the balance fitness function, perform the balance optimization under the spatial resource damage mark, and complete the planning indicator allocation optimization according to the balance optimization result and flow monitoring result.

[0030] Specifically, the equilibrium fitness function is a mathematical function used to measure the degree of balance of spatial resources under different states. First, configure the equilibrium fitness function to determine the variables it contains (such as resource supply and demand, ownership ratio, etc.) and their weights. When configuring the equilibrium fitness function, the relevant factors of economic, ecological, and social values ​​are included in the function variables. For example, economic value may include the input-output ratio of land development, ecological value may include the maintenance level of ecosystem service functions, and social value may include the public's accessibility to spatial resources. Then, perform the equilibrium optimization under the damaged spatial resource mark, and adjust the values ​​of relevant variables using optimization algorithms (such as genetic algorithms and simulated annealing algorithms) according to the economic, ecological, and social value losses reflected by the damaged mark, so that the equilibrium fitness function reaches the optimal value. For example, if it is found that the ecological value of a certain area is damaged due to overdevelopment (such as the reduction of green space), the ecological value-related variables in the equilibrium fitness function will be adjusted during the equilibrium optimization process, the green space planning indicators will be increased, and the indicators of some development projects with greater ecological impact will be reduced. Finally, according to the optimization results, the planning indicator allocation is adjusted to form the final planning indicator optimization plan.

[0031] Through balancing and optimizing, the allocation of planning indicators is optimized according to the actual situation of spatial resources (especially the damage situation), which improves the rationality and effectiveness of planning in many aspects such as economy, ecology and society, and promotes the sustainable development of spatial resources.

[0032] Furthermore, in step S5, flow monitoring of space resource flow processing is established, and flow monitoring results are established, including: Step S51: deploy intelligent terminals, use the intelligent terminals to monitor the flow of space resources, and establish real-time data sets.

[0033] Step S52: Preprocess the real-time data set through edge computing nodes distributed in smart terminals and use it as the first flow data.

[0034] Step S53: Perform resource interaction monitoring on the space resources, and establish second flow data based on the resource interaction monitoring results.

[0035] Step S54: construct a flow monitoring result according to the first flow data and the second flow data.

[0036] Specifically, smart terminals refer to devices with data collection, processing and transmission functions, such as IoT sensors, smart cameras, mobile terminals, etc. Smart terminals are deployed at key locations (such as traffic nodes, building entrances, and near public facilities) to monitor the flow of spatial resources. Smart terminals collect data in real time through sensors (such as cameras, infrared sensors, RFID readers, etc.), such as information on the flow of people, vehicles, and logistics. The collected real-time data is stored locally or in the cloud to form a real-time data set.

[0037] After the smart terminal collects the real-time data set, the edge computing node will pre-process the data, including data cleaning (removing noise data), data compression (reducing the amount of data), feature extraction (extracting key information), etc. For example, the collected personnel flow data is preliminarily screened and format converted to remove invalid data, and the data format is unified into a form that is convenient for subsequent analysis to obtain the first flow data.

[0038] Resource interaction refers to the interaction between spatial resources, such as the impact of land development on the surrounding ecology, the impact of commercial activities on residents' lives, etc. Through sensor networks or data analysis models, the interaction between spatial resources, such as land development intensity and ecological footprint, is monitored. The monitoring results are organized into second flow data and stored in the digital twin platform. Through resource interaction monitoring, the dynamic changes of spatial resource flows can be fully understood, providing richer data for subsequent analysis.

[0039] The first flow data (real-time monitoring data) and the second flow data (interactive monitoring data) are integrated to obtain a complete flow monitoring data set and generate flow monitoring results. By integrating data from different sources, a comprehensive and accurate flow monitoring result can be constructed, which can provide a complete data basis for the subsequent establishment of damaged space resource identification, thereby better managing and optimizing the flow process of space resources.

[0040] Further, such as Figure 2 As shown, in step S5, the loss identification channel is used to compare the flow monitoring result and the resource allocation result to establish a space resource damage mark, including: Step S55: calling the planned loss identification layer of the loss identification channel, and establishing an identification loss result according to the resource configuration result.

[0041] Step S56: calling the comparison and identification layer of the loss identification channel, using the comparison and identification layer to perform planning comparison of the resource configuration result and the second flow data, and establishing a planning comparison and identification result.

[0042] Step S57: Call the strength identification layer of the loss identification channel, perform development strength trigger identification of the second flow data, and establish a development strength trigger identification result.

[0043] Step S58: Quantify the damaged value based on the identified loss result, the planning comparison identification result and the development intensity trigger identification result to establish a damaged space resource identification.

[0044] Specifically, the loss identification channel is a multi-layered algorithm model used to identify and quantify the possible losses of spatial resources during the flow, adjustment or configuration process. It mainly includes three main functional layers: planning loss identification layer, comparison identification layer and intensity identification layer. Among them, the planning loss identification layer takes the resource allocation results (including rigid configuration and elastic configuration) as input data, identifies potential loss risks such as ecological damage and social value reduction by analyzing the resource allocation results, and outputs the identification loss results (i.e. potential loss information), which can be generated based on training of rule engines, threshold models, risk assessment models, etc. The comparison identification layer takes the resource allocation results and the second flow data (such as actual development intensity and resource interaction) as input data, identifies the differences between the resource allocation results and the actual flow monitoring data by comparing them, and outputs the planning comparison identification results (i.e. specific difference information). The intensity identification layer takes the second flow data (such as development intensity and resource interaction frequency) as input data, identifies the development intensity exceeding the preset threshold by analyzing whether the resource development intensity exceeds the preset threshold, and outputs the development intensity trigger identification results (i.e. whether the resource development intensity exceeds the preset threshold).

[0045] When training the loss identification channel, first collect data related to spatial resources, including resource allocation data, such as planned use, land development intensity, infrastructure layout, etc.; flow monitoring data corresponding to resource allocation data, including first flow data and second flow data. Label the collected data. According to professional knowledge and actual conditions, determine which resource allocation results and flow monitoring data have losses and the type and extent of the losses. For example, if the ecological land planned in the resource allocation is encroached upon for commercial development, it is marked as having ecological value loss, and the extent of the loss (such as slight, moderate, severe, etc.) is determined. These labeled data will be used as the target value for training.

[0046] Next, the basic framework of the loss identification channel is constructed, and the collected data is used for training. Exemplarily, for the planning loss identification layer, the labeled resource configuration data is used as training data, and a supervised learning algorithm (such as decision tree, support vector machine SVM) is used to train the model so that it can learn how to identify the difference between resource configuration and planning goals based on the training data. For the comparative identification layer, the labeled resource configuration results and flow monitoring data are used as training data, and a regression model or K nearest neighbor algorithm is used to discover deviation problems in the resource flow process, and the matching accuracy is continuously optimized through the training model. For the intensity identification layer, the development intensity (such as building area, building height, etc.) in the second flow data and the planning development standards are used as training data, and a deep learning model (such as a convolutional neural network or a recurrent neural network) is used to identify whether the development behavior meets the planning requirements. The training process adjusts the model weights so that it can accurately identify development behaviors that exceed the standards.

[0047] During the model training process, a portion of the data that is not involved in the training (test data) is used to evaluate the trained model. Evaluation indicators can include accuracy, recall, F1 value, etc. If the evaluation result of the model is not ideal, the model is optimized. The optimization methods include adjusting the model structure (such as increasing the number of neurons, adjusting the number of layers, etc.), adjusting the training parameters (such as learning rate, number of iterations, etc.), and then retraining until the model achieves satisfactory performance.

[0048] Integrate the planning loss identification layer, comparison identification layer and strength identification layer into the loss identification channel to ensure data flow and collaborative work between the layers. Finally, deploy the constructed loss identification channel to the digital twin platform, configure the flow monitoring data interface and resource configuration data interface, receive data in real time and output damaged identification.

[0049] In the process of establishing the spatial damage identification, the planning loss identification layer of the loss identification channel is first called, and the resource allocation results are input into the planning loss identification layer to identify the losses caused by the resource allocation not meeting the expected plan, and to establish the identification loss results. For example, if the resource allocation results specify the ecological land ratio of a certain area, the planning loss identification layer will determine whether there is a deviation from this plan based on the actual situation (such as land use changes, development activities, etc.), as well as the possible loss of ecological value, economic value or social value caused by such deviation, and generate the identification loss results.

[0050] Next, the comparison and recognition layer of the loss recognition channel is called to compare the resource allocation results with the second flow data, identify the unreasonable adjustments that may occur in the resource flow process, and establish the planning comparison and recognition results. For example, the building density of a commercial area in the plan is compared with the actual monitored construction conditions. If the actual building density exceeds the planned value, the comparison and recognition layer will record this difference and organize it into a planning comparison and recognition result.

[0051] Then, the intensity recognition layer of the loss recognition channel is called to analyze the development-related data in the second flow data (such as the speed and scale of building development, etc.), check whether the second flow data meets the development intensity required by the plan, and establish the development intensity trigger recognition result. For example, for a real estate project under development, the intensity recognition layer will determine whether the actual development speed exceeds the set development intensity threshold (such as the annual upper limit of the building area growth rate, etc.), and if it exceeds this threshold, this situation will be recorded as the development intensity trigger recognition result.

[0052] Finally, the loss identification channel conducts a comprehensive analysis based on the identification results of the three identification layers (identification loss results, planning comparison identification results, and development intensity trigger identification results) to quantify the impact of each type of loss on spatial resources. For example, the identification loss results show that there is a loss in the ecological land planning of a certain area, the planning comparison identification results show that the actual building area exceeds the planned value, and the development intensity trigger identification results show that the development speed is too fast. In the quantitative calculation of the damaged value, the impact of these factors on the ecological value, economic value and social value will be comprehensively considered and converted into quantifiable values ​​or levels, thereby establishing a spatial resource damage identification, which can provide a basis for subsequent resource adjustment and optimization.

[0053] Through the various levels of identification functions of the loss identification channel, various losses in the process of spatial resource flow, allocation and development can be fully identified. This multi-level, all-round loss identification mechanism can accurately capture potential problems in resource allocation and flow, and conduct a comprehensive assessment of possible resource damage, providing accurate reference and basis for subsequent resource adjustments, and promoting the adjustment of resource allocation and the optimization of planning indicators.

[0054] Further, step S58 includes: Step S581: Obtain the damaged area according to the marked loss result, the planning comparison identification result and the development intensity trigger identification result, and calculate the ecological loss value using the damaged area and unit ecological integral.

[0055] Step S582: Analyze the impact on population and quality of life losses based on the identified loss results, the planning comparison identification results, and the development intensity trigger identification results, and establish a social value loss value.

[0056] Step S583: Complete the quantitative calculation of the damaged value according to the ecological loss value and the social value loss value.

[0057] Specifically, the specific damaged areas and areas are determined based on the identification loss results, planning comparison identification results, and development intensity trigger identification results. For example, the area where the actual building area exceeds the planned value is obtained from the planning comparison identification results, and the unplanned land area that is additionally occupied due to overdevelopment is obtained from the development intensity trigger identification results, and these areas are summarized to obtain the damaged area. Then, the ecological loss value is calculated using the predetermined unit ecological integral. Assuming that the unit ecological integral is set to a certain ecological value score per square meter of ecological area, the ecological loss value = damaged area × unit ecological integral. By calculating the ecological loss value, the loss of ecological value caused by development activities can be quantified, providing a scientific basis for subsequent compensation and optimization.

[0058] According to the results of the identification loss and the planning comparison identification, the specific number of people affected by the damage to spatial resources (such as the reduction of public space, the deterioration of the living environment, etc.) is determined, and the impact of development activities on the quality of life of residents, such as noise level, traffic convenience, and the availability of public facilities, is evaluated. Combined with the affected population and the loss of quality of life, the social value loss value is calculated through a preset weight model. For example, in a community renovation, the identification loss results show that the public space is reduced, the affected population is 1,000 people, and the weight of the quality of life loss (assessed according to the degree of impact of the reduction of public space) is 0.5 social value units per person. The social value loss value is calculated as: social value loss value = 1000 × 0.5 = 500 social value units. By establishing the social value loss value, the loss of social value (especially the impact on population and quality of life) caused by the damage to spatial resources can be quantified, providing a quantitative basis for the comprehensive assessment of the damage to spatial resources in terms of social value.

[0059] The ecological loss value and social value loss value are integrated, and weighted calculation is performed through the preset weight model to obtain the total damaged value. Total damaged value = α × ecological loss value + β × social value loss value, where α and β are weighting coefficients, indicating the relative importance of ecological loss and social value loss, which can be customized by the user. Then, based on the quantitative calculation results, a spatial resource damage mark is generated to clarify the type and degree of loss. By integrating the ecological loss value and the social value loss value, a comprehensive quantitative calculation of the damaged value of spatial resources is completed. The established spatial resource damage mark can accurately reflect the damage to the ecological and social values ​​of spatial resources, providing an important basis for subsequent resource management and optimization.

[0060] Furthermore, in step S6, a balanced fitness function is configured to perform balanced optimization under the spatial resource damage indicator, including: Step S61: The equilibrium fitness function is as follows: ;in, Characterizes the equilibrium fitness value, Characterize economic loss measures, Represents the social impact coefficient, Characterize the ecological environment cost, Characterize resource recovery resilience, , , , is the weight coefficient of the corresponding parameter item.

[0061] Step S62: After the initial parameter set is established, the equilibrium fitness function is used to evaluate the fitness of the initial parameter set, and a cumulative update constraint is established according to the fitness evaluation result.

[0062] Step S63: Iterate the initial parameter set through the cumulative update constraint, and complete the balance optimization according to the iteration result.

[0063] Specifically, the above equilibrium fitness function comprehensively considers multiple dimensions such as economic losses, social impacts, ecological environmental costs, and resource recovery elasticity. By weighted summing economic losses, social impacts, ecological costs, and resource recovery elasticity, a equilibrium fitness value is generated to evaluate the comprehensive performance of resource allocation. When calculating the equilibrium fitness, first quantify the economic loss metric according to planning needs. , social impact coefficient , Ecological and environmental costs and resource resilience The initial parameter values ​​and the weight coefficients corresponding to these parameters , , , , generate the initial parameter set. Exemplary, economic loss metric It can be determined by comparing the economic value of space resources before and after damage (such as land transfer price, rental income, etc.); social impact coefficient It can be obtained through questionnaire surveys, social welfare indicators, etc.; ecological environmental cost It can be calculated with the help of ecological value assessment model; resource recovery elasticity Can be evaluated based on historical data or simulation experiments; weight coefficient , , , These initial parameter values ​​can be assigned according to the importance of each dimension through expert scoring, analytic hierarchy process (AHP) or other multi-criteria decision-making methods, and these initial parameter values ​​can be substituted into the equilibrium fitness function Calculate and determine the fitness evaluation result of the initial parameter set, that is, the equilibrium fitness value Based on the fitness evaluation results, analyze which parameters have a greater impact on fitness and establish cumulative update constraints. For example, if the economic loss metric is found If the fitness is greatly affected and the current value leads to a lower fitness, then a measure of economic loss can be established. The update constraints are set, such as limiting the increase or specifying the direction of adjustment. Through fitness evaluation and establishing cumulative update constraints, an initial evaluation and constraint framework is provided for the subsequent iterative optimization process, which helps to improve the efficiency and accuracy of the optimization process and make the optimization process more targeted in the direction of improving the overall balance fitness of spatial resources.

[0064] According to the conditions of the cumulative update constraint, the initial parameter set is iterated using an optimization algorithm (such as a genetic algorithm, simulated annealing algorithm, etc.). For example, if the cumulative update constraint stipulates that the economic loss metric In each iteration, only a certain proportion can be reduced. Then, in each iteration, adjust according to this constraint. The social impact coefficient can also be adjusted according to other constraints. , Ecological and environmental costs and resource resilience And the weight coefficient , , , Then substitute the adjusted parameter set into the equilibrium fitness function again to calculate the new fitness value, and adjust the resource allocation according to the updated result to find the value that makes The optimal resource allocation scheme that is maximized. Repeat this process until a certain stopping condition is met (such as the fitness value reaches the predetermined target value, the number of iterations reaches the upper limit, etc.).

[0065] By iterating the initial parameter set and completing the balanced optimization according to the iteration results, a set of optimal parameter values ​​(including economic loss measurement, social impact coefficient, ecological environmental cost, resource recovery elasticity and weight coefficient, etc.) can be found to make the value of the balanced fitness function reach the optimal or near-optimal value, thereby providing the best parameter setting scheme for the management and optimization of space resources, which is helpful to improve the overall balance and sustainable development capabilities of space resources in economic, social, ecological and other aspects.

[0066] Furthermore, in step S6, the planning indicator allocation optimization is completed according to the balance optimization result and the flow monitoring result, and further includes: Step S64: establishing a feedback data set for planning indicator allocation according to the spatial resource damage identification and the flow monitoring result.

[0067] Step S65: performing feedback impact analysis on the feedback data set, and when the feedback impact analysis result triggers a preset impact threshold, generating configuration feedback of resource configuration according to the feedback impact analysis result.

[0068] Step S66: reconstructing the resource configuration result according to the configuration feedback, and completing the planning indicator allocation optimization according to the reconstructed resource configuration result.

[0069] Specifically, first, relevant information is extracted from the damaged space resource identification, such as the damaged area, the quantified results of the damaged value, and other data, and data such as the resource flow speed and resource flow direction are obtained from the flow monitoring results. Then these data are integrated according to certain rules and formats to form a feedback data set, which provides a comprehensive information source for a comprehensive understanding of the status of space resources.

[0070] The feedback data set is analyzed using data analysis methods. For example, statistical analysis methods can be used to analyze the correlation between various indicators in the data set, or model analysis methods (such as regression models based on multiple factors, etc.) can be used to evaluate the impact of various data on resource allocation. The impact results obtained by the analysis are compared with the preset impact threshold. This preset impact threshold is a standard value for measuring the impact level set in advance. When the feedback impact analysis results reach or exceed this threshold, corresponding measures need to be taken to generate configuration feedback for resource allocation. For example, if the analysis results show that the ecological and environmental costs of a certain area are too high due to the damage to spatial resources, affecting the balance of overall resource allocation, when this impact exceeds the preset threshold, the configuration feedback may be to increase the ecological resource investment in the area or adjust the development plan of the area. Through feedback impact analysis, the significant impact of spatial resource status on resource allocation can be discovered in a timely manner. When the impact reaches a certain level (triggering the preset impact threshold), the generated configuration feedback can provide a scientific basis for the adjustment of resource allocation and further optimize spatial resource allocation.

[0071] According to the adjustment suggestions in the configuration feedback, modify the various indicators in the resource allocation results. For example, if the configuration feedback suggests adding ecological land indicators in a certain area, then when reconstructing the resource allocation results, adjust the ecological land proportion and other indicators in the land use planning accordingly. On the basis of reconstructing the resource allocation results, reallocate the planning indicators according to the optimized resource allocation plan. By reconstructing the resource allocation results to optimize the allocation of planning indicators, the scientificity and rationality of resource allocation can be improved, better adapt to the actual status of spatial resources, and promote the sustainable use and development of spatial resources.

[0072] Furthermore, after completing the optimization of planning indicator allocation according to the balance optimization results and flow monitoring results, it also includes: Step S71: Establish the flow monitoring results and the spatial resource damage identification as a time series data set.

[0073] Step S72: Perform time series development forecast on the time series data set and establish trend warning results.

[0074] Step S73: matching an emergency response mechanism according to the trend warning result, and performing warning optimization processing according to the emergency response mechanism.

[0075] Specifically, first, determine the recording unit of time (such as day, month, year, etc.). Then, integrate the flow monitoring results and the data in the space resource damage identification according to this time unit. For example, if the flow monitoring result is to monitor the flow speed and flow of resources once a day, and the space resource damage identification is also updated and evaluated once a day, then the flow monitoring results and space resource damage identification data of the same day can be combined to form a time series data point. Arrange multiple such time series data points in chronological order to construct a time series data set, which can reflect the dynamic changes of space resources over time.

[0076] Based on the time series data set, statistical analysis or machine learning methods are used to predict the development trend of space resources in the future, including the changing trends in the flow status and damage of space resources. A variety of methods can be used to predict the development of time series. For example, traditional statistical methods such as moving average method and exponential smoothing method can be used to predict future values ​​by weighted average and other operations on the data in the time series data set. Machine learning methods such as long short-term memory network can also be used to train models with time series data sets as input to predict the development trend of space resources in the future. According to the prediction results, trend warning results are established. For example, if the prediction results show that the resource development intensity of a certain area will exceed the ecological carrying capacity in the next three months, this result will be recorded as a trend warning result. Establishing trend warning results through time series development prediction can detect possible problems of space resources in advance, provide warning information for taking corresponding measures, and help improve the foresight of space resource management and protection.

[0077] According to the trend warning results, the matching emergency response mechanism is searched in the pre-set emergency response mechanism library. The emergency response mechanism library stores pre-made response plans for different trend warning results, including measures to be taken when resources are in emergency (such as ecological crisis, over-exploitation of resources, etc.), such as adjusting resource development plans, launching resource restoration projects, etc. The warning information is optimized according to the matching emergency response mechanism. For example, according to the requirements of the emergency response mechanism, the level, scope, time and other parameters of the warning are adjusted to ensure that the warning information can be accurately conveyed to relevant departments and personnel, so that the response measures can be implemented more effectively.

[0078] By matching the emergency response mechanism to optimize early warning processing, the effectiveness of early warning information and the pertinence of response measures can be improved, so that space resource management can respond more promptly and effectively when facing potential risks, thereby protecting the sustainable development of space resources.

[0079] In summary, the planning indicator allocation optimization method in the stock planning environment provided by the embodiment of the present application has the following technical effects: By using drone aerial surveying and data interaction to build a digital twin platform for space resources, a high-precision, visual digital model is provided for stock space resources, and comprehensive digital management of space resources is realized, thereby providing accurate data support for subsequent ownership confirmation, value assessment, resource allocation and dynamic monitoring. The digital twin platform for space resources is used to confirm multi-dimensional ownership, ensuring that the property rights of space resources are clear and definite, and avoiding ownership disputes; the evaluation network is used to conduct a comprehensive evaluation of space resources from the three dimensions of economy, society and ecology, and establish scientific evaluation results, which provides an important basis for resource allocation, so that resource allocation can comprehensively consider multiple values ​​and avoid the irrationality caused by single-dimensional evaluation. According to the evaluation results and ownership confirmation, a combination of rigidity and flexibility is implemented for resource allocation. Rigid configuration ensures the basic requirements and bottom line of planning, while flexible configuration reserves space for future development and dynamic adjustment. Through the spatial resource flow processing and ownership adjustment of the three-level market, resource allocation is further optimized to make it more adaptable to market demand and urban development dynamics. The flow of space resources is monitored in real time through smart terminals and edge computing nodes, and flow monitoring results are established. At the same time, the loss identification channel is used to compare and analyze the resource allocation results and flow monitoring results, and a spatial resource damage mark is established, so that problems and potential risks in resource allocation can be discovered in a timely manner, providing data support for subsequent optimization and adjustment. By configuring the equilibrium fitness function to quantify multiple dimensions such as economic losses, social impacts, and ecological and environmental costs, the resource allocation plan is dynamically adjusted to achieve the optimal balance state, ensuring the scientificity and adaptability of planning indicator allocation, and being able to effectively respond to the complex and changing stock planning environment. Through feedback data set analysis and time series prediction, a trend warning mechanism is established, which can not only adjust resource allocation according to real-time data, but also predict future development trends, take optimization measures in advance, and further improve the foresight and scientific nature of planning.

[0080] Overall, the embodiments of the present application achieve efficient allocation and optimized management of spatial resources through the synergy of the above-mentioned links, significantly improve the rationality of spatial resource allocation and spatial resources under the existing planning environment, enhance the scientificity, adaptability and flexibility of planning indicator allocation, and provide strong support for the sustainable development of the city.

[0081] Embodiment 2, as Figure 3 As shown, based on the same inventive concept as the above-mentioned embodiment 1, the embodiment of the present application provides a planning indicator allocation optimization system in a stock planning environment, and the system includes: The twin platform module 10 is used to build a space resource digital twin platform, which is constructed through drone aerial survey collection and data interaction.

[0082] The three-dimensional value assessment module 20 is used to use the spatial resource digital twin platform to perform multi-dimensional ownership confirmation, and use the assessment network to perform three-dimensional value assessment of spatial resources to establish assessment results.

[0083] The resource configuration module 30 is used to configure resources according to the evaluation results and the multi-dimensional ownership confirmation results, and establish resource configuration results. The resource configuration includes rigid configuration and flexible configuration.

[0084] The ownership adjustment module 40 is used to process the spatial resource flow of the tertiary market using the resource allocation results, and to adjust the ownership according to the multi-dimensional ownership confirmation results.

[0085] The flow monitoring module 50 is used to establish flow monitoring of space resource flow processing, establish flow monitoring results, use the loss identification channel to compare the flow monitoring results and the resource allocation results, and establish a space resource damage mark.

[0086] The balance optimization module 60 is used to configure the balance fitness function, perform balance optimization under the spatial resource damage mark, and complete the planning indicator allocation optimization according to the balance optimization result and the flow monitoring result.

[0087] Furthermore, the flow monitoring module 50 of the embodiment of the present application is also used to perform the following steps: Deploy smart terminals, use the smart terminals to monitor the flow of space resources, and establish real-time data sets; use the edge computing nodes distributed on the smart terminals to perform data preprocessing on the real-time data sets as first flow data; perform resource interaction monitoring on space resources, and establish second flow data based on the resource interaction monitoring results; construct flow monitoring results based on the first flow data and the second flow data.

[0088] Furthermore, the flow monitoring module 50 of the embodiment of the present application is also used to perform the following steps: Call the planning loss identification layer of the loss identification channel, and establish an identification loss result according to the resource allocation result; call the comparison identification layer of the loss identification channel, and use the comparison identification layer to perform planning comparison of the resource allocation result and the second flow data to establish a planning comparison identification result; call the strength identification layer of the loss identification channel, execute the development intensity trigger identification of the second flow data, and establish a development intensity trigger identification result; perform quantitative calculation of the damaged value according to the identification loss result, the planning comparison identification result and the development intensity trigger identification result, and establish a damaged identification of spatial resources.

[0089] Furthermore, the flow monitoring module 50 of the embodiment of the present application is also used to perform the following steps: The damaged area is obtained according to the identified loss results, the planning comparison and identification results, and the development intensity trigger identification results, and the ecological loss value is calculated using the damaged area and unit ecological points; the impact on population and quality of life loss is analyzed according to the identified loss results, the planning comparison and identification results, and the development intensity trigger identification results, and the social value loss value is established; the quantitative calculation of the damaged value is completed according to the ecological loss value and the social value loss value.

[0090] Furthermore, the balancing optimization module 60 in the embodiment of the present application is also used to perform the following steps: The equilibrium fitness function is as follows: ;in, Characterizes the equilibrium fitness value, Characterize economic loss measures, Represents the social impact coefficient, Characterize the ecological environment cost, Characterize resource recovery resilience, , , , is the weight coefficient of the corresponding parameter item; after the initial parameter set is established, the fitness of the initial parameter set is evaluated using the balanced fitness function, and a cumulative update constraint is established according to the fitness evaluation result; the initial parameter set is iterated through the cumulative update constraint, and the balanced optimization is completed according to the iterative result.

[0091] Furthermore, the balancing optimization module 60 in the embodiment of the present application is also used to perform the following steps: A feedback data set for planning indicator allocation is established based on the spatial resource damage identification and the flow monitoring results; feedback impact analysis of the feedback data set is performed, and when the feedback impact analysis result triggers a preset impact threshold, configuration feedback for resource configuration is generated based on the feedback impact analysis result; resource configuration results are reconstructed based on the configuration feedback, and planning indicator allocation optimization is completed based on the reconstructed resource configuration results.

[0092] Furthermore, the system described in the embodiment of the present application is also used to perform the following steps: The flow monitoring results and the spatial resource damage identification are established as a time series data set; the time series development forecast is performed on the time series data set to establish a trend warning result; the emergency response mechanism is matched according to the trend warning result, and the warning optimization processing is performed according to the emergency response mechanism.

[0093] Through the above-mentioned detailed description of the planning indicator allocation optimization method in the stock planning environment in this specification, those skilled in the art can clearly understand the planning indicator allocation optimization system in the stock planning environment in this embodiment. For the system disclosed in Example 2, since it corresponds to the method disclosed in Example 1 and has corresponding functional modules and beneficial effects, the relevant parts can be referred to the method part description.

[0094] The above description of the disclosed embodiments enables those skilled in the art to implement or use the present application. Various modifications to these embodiments will be apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present application. Therefore, the present application will not be limited to the embodiments shown herein, but will conform to the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. The planning indicator allocation optimization method in the stock planning environment is characterized by: The method comprises: Building a digital twin platform for space resources, which is constructed through drone aerial survey collection and data interaction; The digital twin platform of spatial resources is used to confirm multi-dimensional ownership, and the evaluation network is used to evaluate the three-dimensional value of spatial resources and establish evaluation results; Perform resource allocation based on the evaluation results and multi-dimensional ownership confirmation results, and establish resource allocation results, where the resource allocation includes rigid allocation and flexible allocation; Use the resource allocation results to process the spatial resource flow in the tertiary market, and adjust the ownership according to the multi-dimensional ownership confirmation results; Establishing flow monitoring of space resource flow processing, establishing flow monitoring results, using a loss identification channel to compare the flow monitoring results and the resource allocation results, and establishing a space resource damage identification; Configure the balance fitness function, perform balance optimization under the identification of damaged spatial resources, and complete the planning indicator allocation optimization based on the balance optimization results and flow monitoring results.

2. The planning indicator allocation optimization method in the stock planning environment according to claim 1, characterized in that: The establishing of flow monitoring of space resource flow processing and establishing flow monitoring results include: Deploy intelligent terminals, use the intelligent terminals to monitor the flow of space resources, and establish real-time data sets; After the real-time data set is pre-processed by edge computing nodes distributed in smart terminals, it is used as the first flow data; Perform resource interaction monitoring on space resources, and establish second flow data based on the resource interaction monitoring results; A flow monitoring result is constructed according to the first flow data and the second flow data.

3. The planning indicator allocation optimization method in the stock planning environment according to claim 2, characterized in that: The using the loss identification channel to compare the flow monitoring result and the resource allocation result to establish a space resource damage identification includes: Calling the planned loss identification layer of the loss identification channel to establish an identification loss result according to the resource configuration result; Calling the comparison and identification layer of the loss identification channel, using the comparison and identification layer to perform planning comparison of the resource configuration result and the second flow data, and establishing a planning comparison and identification result; Calling the strength identification layer of the loss identification channel to perform development strength trigger identification of the second flow data and establish a development strength trigger identification result; The damaged value is quantified based on the identified loss results, the planning comparison identification results and the development intensity trigger identification results to establish a damaged space resource identification.

4. The planning indicator allocation optimization method in the stock planning environment according to claim 3 is characterized in that: The quantitative calculation of the damaged value according to the identification loss result, the planning comparison identification result and the development intensity trigger identification result includes: Obtaining the damaged area according to the marked loss result, the planning comparison identification result and the development intensity trigger identification result, and calculating the ecological loss value using the damaged area and unit ecological integral; Conducting population and quality of life loss analysis based on the identified loss results, the planning comparison identification results, and the development intensity trigger identification results, and establishing a social value loss value; The quantitative calculation of the damaged value is completed based on the ecological loss value and social value loss value.

5. The planning indicator allocation optimization method in the stock planning environment according to claim 1, characterized in that: The configuration balance fitness function performs a balance optimization under the space resource damage mark, including: The equilibrium fitness function is as follows: ； in, Characterizes the equilibrium fitness value, Characterize economic loss measures, Represents the social impact coefficient, Characterize the ecological environment cost, Characterize resource recovery resilience, , , , is the weight coefficient of the corresponding parameter item; After the initial parameter set is established, the fitness of the initial parameter set is evaluated using the equilibrium fitness function, and a cumulative update constraint is established according to the fitness evaluation result; The initial parameter set is iterated through the cumulative update constraint, and the balance optimization is completed according to the iteration result.

6. The planning indicator allocation optimization method in the stock planning environment according to claim 1, characterized in that: The optimization of planning indicator allocation is completed according to the balance optimization result and the flow monitoring result, and further includes: Establishing a feedback data set for planning indicator allocation according to the spatial resource damage identification and the flow monitoring result; Performing feedback impact analysis on the feedback data set, and when a feedback impact analysis result triggers a preset impact threshold, generating configuration feedback of resource configuration according to the feedback impact analysis result; The resource configuration result is reconstructed according to the configuration feedback, and the planning indicator allocation optimization is completed according to the reconstructed resource configuration result.

7. The planning indicator allocation optimization method in the stock planning environment according to claim 1, characterized in that: After the planning indicator allocation optimization is completed according to the balance optimization result and the flow monitoring result, the following is further included: Establishing the flow monitoring results and the spatial resource damage identification as a time series data set; Perform time series development forecast on the time series data set and establish trend warning results; An emergency response mechanism is matched according to the trend warning result, and warning optimization processing is performed according to the emergency response mechanism.

8. The planning indicator allocation optimization system in the stock planning environment is characterized by: The system is used to execute the planning indicator allocation optimization method in the stock planning environment according to any one of claims 1 to 7, comprising: The twin platform module is used to build a digital twin platform for space resources, which is constructed through drone aerial survey collection and data interaction; A three-dimensional value assessment module, which is used to use the digital twin platform of spatial resources to perform multi-dimensional ownership confirmation, and use the assessment network to perform three-dimensional value assessment of spatial resources to establish assessment results; A resource configuration module, used to configure resources according to the evaluation results and the multi-dimensional ownership confirmation results, and establish resource configuration results, wherein the resource configuration includes rigid configuration and flexible configuration; The ownership adjustment module is used to process the spatial resource flow of the tertiary market using the resource allocation results, and to adjust the ownership according to the multi-dimensional ownership confirmation results; A flow monitoring module, used to establish flow monitoring of space resource flow processing, establish flow monitoring results, compare the flow monitoring results and the resource allocation results using a loss identification channel, and establish a space resource damage mark; The balance optimization module is used to configure the balance fitness function, perform balance optimization under the spatial resource damage mark, and complete the planning indicator allocation optimization based on the balance optimization results and flow monitoring results.

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