54 results about "Socio economic data" patented technology

The invention discloses a water network dam overtopping flooding simulation and disaster damage assessment method, and belongs to the technical field of flood control and disaster reduction. The method comprises the following steps: performing hydrodynamic analysis based on hydrological geographic data, and determining a potential overtopping area; for the potential overtopping area, simulating breach evolution based on a cumulative scouring energy criterion, and generating a breach flow process; simulating flood routing according to the breach flow process, and generating a spatialized disaster intensity field; and in combination with the disaster intensity field and social economic data, direct and indirect economic losses are evaluated, and a comprehensive disaster damage result is generated. According to the method, a physical criterion based on accumulated scouring energy is introduced, a comprehensive strength index, a three-dimensional vulnerability curved surface and an application graph neural network are adopted to simulate cascade failure, and the problems of breach trigger mechanism deficiency, single disaster strength measurement and disaster damage assessment staticization are solved.

The invention provides an intelligent virtuality and reality combined psychological health service device based on digital elements, and aims to improve the accuracy and individuation level of psychological health management. The device firstly obtains the physiological indexes, behavior data, environmental factor data and social economic data of an individual, and carries out multi-modal fusion to form comprehensive feature data. Based on this, a psychological health environment factor model is constructed to quantify the influence of the external environment on the individual psychological state, and the calculation weight and prediction logic of the negative emotion large model are optimized. And the optimized negative emotion large model is used for identifying an individual emotion state, analyzing factors such as social environment, economic pressure and life events in combination with the mental health environment factor model, and generating an individual mental health assessment result. And according to an evaluation result, the virtual digital doctor provides intelligent pre-inquiry and other services. Through data-driven intelligent analysis and virtual-real combined intervention means, the accessibility, accuracy and intervention effect of psychological health services are improved.

The invention discloses a black land water and soil resource bearing capacity evaluation system based on big data, which relates to the technical field of agricultural production and comprises a data acquisition module, a data preprocessing module, an evaluation index calculation module, a bearing capacity evaluation model module and a result analysis and display module. The data acquisition module is used for acquiring soil data, water resource data and social economic data of black land. According to the evaluation system for the bearing capacity of the water and soil resources of the black land, through integration of multi-source heterogeneous data, comprehensive and accurate evaluation of the bearing capacity of the water and soil resources of the black land is achieved, high-density deployment and real-time updating of the data acquisition module are achieved, the temporal-spatial resolution and reliability of an evaluation result are ensured, and the evaluation accuracy is improved. The problem of insufficient data acquisition density in the prior art is effectively solved, a data preprocessing and evaluation model construction technology is adopted, the dynamic adaptability and prediction precision of an evaluation model are improved, and visual and understandable chart display and decision support information are provided.

The invention discloses a multi-dimensional trade-off analysis method for watershed ecological service optimization, which belongs to the technical field of multi-dimensional trade-off analysis, and comprises the following steps: S1, adopting a multi-source heterogeneous data fusion algorithm, combining remote sensing, GIS (Geographic Information System), weather and social economic data, and extracting key ecological factors through a random forest; according to the method, Monte Carlo simulation is utilized to generate multiple groups of land utilization scenes, and key tradeoff pairs are identified in combination with principal component analysis, so that challenges of uncertainty and multi-target conflicts in ecological service optimization are effectively coped with; thousands of groups of land utilization patterns are generated through random sampling, ecological service values under different scenes are simulated, and the limitation of single scene hypothesis is avoided; principal component analysis eliminates dimensional differences through standardization processing, extracts dominant ecological service types, and provides a mathematical basis for quantification of a tradeoff relationship.

The invention discloses an intelligent redevelopment research method for low-efficiency land use, which comprises the following steps of: acquiring multi-source data including land change survey data, topographic data, urban planning data, remote sensing data, point-of-interest data, mobile signaling data and social economic data in a research area, and inputting the multi-source data into a land use identification model; obtaining a spatial distribution diagram of low-efficiency land in the research area and corresponding low-efficiency factors; inputting the spatial distribution diagram and the low-efficiency factors into a redevelopment potential calculation model to obtain a redevelopment comprehensive potential value of the low-efficiency land; a plurality of redevelopment schemes are obtained based on the redevelopment comprehensive potential value, the rigid constraint of the low-efficiency land during redevelopment and the redevelopment mode library; and obtaining respective corresponding benefit index difference values after the low-efficiency land is redeveloped by using the plurality of redevelopment schemes, and obtaining an optimal redevelopment scheme from the plurality of redevelopment schemes by using a multi-attribute decision algorithm and the benefit index difference values.

The invention belongs to the technical field of water quality monitoring, and discloses a big data water quality dynamic monitoring and early warning method and system, a'water environment-social economy-ecosystem 'ternary data system is constructed through a cross-domain data symbiosis module, social and economic data such as enterprise pollution discharge, agricultural irrigation and the like and ecological microscopic data such as algae gene expression and the like are fused, and the water quality dynamic monitoring and early warning system is established. Implicit factor dominance is realized in combination with a dynamic weight algorithm; meanwhile, the quantum dot marking technology breaks through chemical analysis blind areas, accurately locates multi-source pollution, greatly improves the novel combined pollution identification capability, solves the problem that the traditional technology is lagged in response to complex pollution, and provides omnibearing data support for pollution traceability; in extreme weather, a parameter mutation adaptation mechanism is started, sub-models are rapidly switched, and an enhanced feature set generated by a cross-domain feature distillation step is combined, so that the model can accurately simulate the coupling effect of pollutants and a biologic chain, the long-term prediction stability is remarkably improved, and a reliable trend basis is provided for early warning decision making.

The invention discloses an industrial chain node anomaly detection method and system based on electric power time sequence characteristics, and belongs to the technical field of industrial chain data processing, and the method comprises the steps: obtaining electric power data, social and economic data of different industries, and upstream and downstream associated data in the industries in real time; performing season adjustment on the index time sequence in the primary selection index pool by using a time sequence model; performing association analysis to obtain an industrial node association rule, analyzing a time difference earlier stage or lagging stage of indexes of upstream and downstream nodes according to the industrial node association rule, and dividing into consistent, first and lagging index groups; calculating a diffusion index and a synthesis index, and analyzing supply and demand conduction indexes of upstream and downstream of the industry to form a prosperity sequence; comparing the distribution difference between the current sequence and the reference business sequence through KS test to judge whether abnormity exists or not; and tracing the source link with the abnormal condition according to the abnormal test result, and quantifying the influence degree of the source link on the whole industry chain.

The invention discloses an atmospheric greenhouse gas delta13C isotope observation construction method, which belongs to the technical field of atmospheric environment monitoring and is realized through three steps of monitoring data acquisition, traceability data acquisition and data processing standardization. According to the invention, through a double-site cooperative monitoring network and in combination with data acquisition of background sites and urban sites, the atmospheric CH4 concentration can be monitored in real time, and the delta 13C isotope value of CH4 can be accurately analyzed. And the source of CH4 can be qualitatively identified by utilizing a Kearing plot model, and high precision and high credibility of source analysis are ensured. According to the method, the Bayesian mixture model and the machine learning technology are adopted, the CH4 emission contributions of different sources are quantitatively estimated, and the emission sources and driving factors of CH4 are comprehensively analyzed in combination with multi-source tracer data and social economic data.

The invention discloses a low-efficiency land use identification method and device based on a pressure-state-response framework, and the method comprises the steps: obtaining the geographic position data, land use type data, social and economic data, population data, ecological environment data, infrastructure data and regulation and control response data of a plurality of target regions; calculating a spatial correlation coefficient between the first target area and the second target area based on the geographic position data, the land use type data, the social economic data and the ecological environment data to obtain a spatial correlation matrix; based on the social economic data, the population data, the ecological environment data, the infrastructure data, the regulation and control response data and the spatial incidence matrix, constructing a low-efficiency land use evaluation index system; determining a comprehensive evaluation index set of each target area through the low-efficiency land use evaluation index system and the land use type data; and determining the low-efficiency land use level of each target area based on the comprehensive evaluation index set, and obtaining a low-efficiency land use identification result. According to the invention, the accuracy of low-efficiency land use identification can be improved.

The invention discloses a land-sea overall land and land space planning method and system, and the method comprises the steps: collecting remote sensing data, marine environment monitoring data and basic geographic and social economic data of a research region, and carrying out the denoising, format conversion and time-space registration preprocessing of the data; fusing the preprocessed data by adopting an enhanced self-adaptive space-time reflectivity fusion model to generate a unified data set with high space-time resolution; constructing a three-level classification system based on the fused data set, carrying out land space suitability dynamic evaluation by adopting an adaptive weighting algorithm, and outputting a classification result and a suitability score; and taking the suitability scoring result as input, performing multi-objective optimization solution by adopting an improved non-dominant genetic algorithm, and generating and outputting a land-sea land space planning scheme. According to the method, the problem of differences of land and sea data in source, format, resolution and updating frequency is effectively solved, a unified space-time reference is established, and the data integration capability and the accuracy of a planning foundation are remarkably improved.

The invention provides an ecological risk evaluation and prediction evaluation method based on a multi-source evaluation framework, and relates to the technical field of ecological risk evaluation, and the method specifically comprises the steps: dividing a target region into grid units, and collecting landscape pattern and environmental social economic data; analyzing landscape data through a sliding window method, and calculating a landscape ecological risk value of each unit; constructing a regional ecological risk assessment index system based on social economic data, determining an index weight by adopting Bayesian BWM and CRITIC methods, and performing weighted calculation to obtain a regional ecological risk value; integrating the two types of risk values to form a spatial distribution diagram, and superposing to obtain a unit comprehensive ecological risk value; and performing risk grading by adopting a natural breakpoint method, generating a grading graph, predicting risk early warning time of each unit based on a historical trend, and realizing ecological risk dynamic evaluation and early warning.

The invention relates to the technical field of drainage networks, in particular to a drainage network siltation risk assessment method based on a random forest algorithm, and the method comprises the steps: obtaining pipeline basic data, siltation detection data, land utilization data and social economic data of a drainage network; constructing a pipeline siltation regression model based on a random forest algorithm and obtaining a pipeline siltation degree; calculating the importance degree of input factors by using an OOB sample during training of the pipeline siltation regression model; calculating a pipeline risk factor according to the importance degree of the input factor, the value of the input factor and the pipeline siltation degree; fitting is conducted on the pipeline siltation degree and the pipeline danger factors through a logistic curve, and a curve fitting result is obtained; and calculating a pipeline risk factor corresponding to a preset pipeline siltation degree based on a curve fitting result, and obtaining a pipeline siltation risk assessment result according to the pipeline risk factor and a preset siltation risk grade. According to the method, multi-dimensional comprehensive assessment of the sedimentation risk of the drainage pipeline is realized, and the efficiency and accuracy of risk assessment are greatly improved.

The invention relates to the technical field of reservoir flood control early warning, and discloses a reservoir flood control risk assessment and early warning system based on big data. A data aggregation unit of the system continuously collects historical hydrology, real-time meteorology, reservoir area geographic information and surrounding social economic data; the data preprocessing unit performs multi-dimensional cleaning and standardization on the data to generate an assessment input data set with a unified format; the risk dynamic analysis unit constructs a flood occurrence probability prediction model by applying a machine learning algorithm on the basis of the data set, constructs a submerging range simulation model in combination with geographic space characteristics, and calculates a potential economic loss quantized value; the early warning grade mapping unit inputs the result into an early warning grading rule base to generate an overall flood control risk early warning grade; a plan matching decision-making unit retrieves a flood control coping plan set with the highest matching degree according to the early warning level; and the early warning information issuing unit converts the pre-arranged plan into visual guidance information, and broadcasts and pushes the visual guidance information to an emergency management department and downstream resident terminals.

The invention discloses a shared bicycle passenger flow prediction method based on a geographically weighted regression model and a related device. The method comprises the following steps: collecting spatial data and social economic data of a shared bicycle putting point of a target city; inputting the effective independent variable data set, the spatial autocorrelation of the effective independent variables, the multi-collinearity test result and the housing price factor data into a least square regression model and a geographical weighted regression model, and outputting a regression coefficient, a significance level and a goodness of fit; and according to the regression coefficient, the significance level, the goodness of fit, the delivery point category and the actual shared bicycle passenger flow data, calculating the prediction precision and the lifting amplitude at different delivery point categories. According to the method, the spatial heterogeneity relationship between the shared bicycle passenger flow volume and the influence factors is considered through the geographically weighted regression model, the regression coefficient is adjusted according to different geographic positions, the influence characteristics of a local area are reflected more accurately, and the prediction precision is remarkably improved.

The invention relates to the technical field of territorial space planning, and provides a territorial space planning risk assessment method which comprises the following steps: step 1, based on a space planning target of a target area, dividing multiple levels of assessment units, and constructing a three-dimensional risk assessment index system comprising a risk source index, a risk bearing body index and a risk conduction path index; 2, collecting multi-source heterogeneous data including remote sensing images, geological and geographic data and social and economic data, and generating a spatial database through data fusion; and step 3, classifying the data by adopting a Jenks natural breakpoint method, calculating an index weight in combination with an empowerment method, and constructing a dynamic risk assessment index matrix. 12 types of indexes are integrated through a risk source-bearing body-conduction path three-dimensional model, and the assessment coverage rate is increased by 40%; multi-scale trend distribution point correction enables the remote sensing image registration error to be reduced to 1.2 pixels, and the disaster identification false alarm rate is reduced by 35%.

The application discloses a kind of building disaster loss evaluation uncertainty optimization method of multi-source data and random distribution coupling, comprising the following steps: collecting the historical flood data of different cities, different types of buildings;The evaluation area is divided into grid;High-resolution water depth data of each grid unit is simulated and generated using HiPIMS model, and disaster loss data of each grid is generated by combining remote sensing data verification;The cost of different types of buildings is generalized using building cost data in city statistical yearbook;Building flood vulnerability is evaluated based on the gridding method;The evaluation uncertainty of building flood vulnerability is quantified using confidence level analysis method.The application solves the problem of multi-source data fusion and building accurate classification, unifies the scale difference of flood characteristics and socio-economic data, introduces confidence level analysis method to quantify uncertainty, significantly improves the evaluation accuracy and reliability, and provides scientific support for urban disaster prevention and mitigation, risk management and planning.

The invention relates to a high-precision particulate matter quantity and concentration prediction method, device and equipment based on Stacking ensemble learning, a storage medium and a program product. The method comprises the steps that to-be-processed data are obtained, and the to-be-processed data comprise environmental data and social economic data; the to-be-processed data is input into a pre-trained stack integration model, a first layer of the stack integration model comprises at least two preselected base learners, and a second layer of the stack integration model comprises a meta learner; processing the to-be-processed data through the at least two preselection base learners to obtain at least two preliminary prediction results of the particle quantity concentration; and processing the at least two preliminary prediction results through the meta-learner to obtain a particle quantity concentration prediction result. The monitoring cost of the particulate matter number concentration can be reduced, and the space coverage rate and the real-time performance of particulate matter number concentration monitoring can be improved.

The invention belongs to the technical field of urban planning, and particularly relates to a traffic station region land utilization efficiency evaluation method, which comprises the following steps of: acquiring and preprocessing point-of-interest data and a traffic station region in an analysis region; extracting land utilization layout features based on the null data set; constructing a multi-mode traffic network including walking, bicycles, buses and rail transit based on the layout features; establishing a land coupling simulation model of traffic based on the regional reachability index; causal inference and model calibration are carried out based on historical traffic intervention events of dynamic evolution; adopting a multi-objective optimization algorithm to generate traffic and land utilization configuration schemes meeting different planning objectives; according to the method, the evaluation result is subjected to visual display and decision output, unified modeling of traffic and social economic data is achieved through multi-source heterogeneous data fusion and standardization processing, and the effect of improving data space-time matching precision and calculation reliability is achieved.

The application relates to a water resource pressure assessment method integrating social economy and climate change. It relates to the technical field of water resource pressure assessment in arid river basins. The method comprises the following steps: obtaining historical values and predicted values of social economic data, correcting the predicted values of the social economy to obtain corrected predicted values; calculating potential evapotranspiration in different scenarios based on historical scenario meteorological data and corrected future climate mode data; calculating future basin water resources based on the correlation between basin rainfall and water resources; extracting drought intensity characteristics according to the change trend of the historical scenario and the future scenario basin drought index; constructing a basin water resource pressure index calculation formula; and according to the calculated water resource pressure index of the water resource region, standardizing the index to obtain a standardized index, and evaluating the change trend of the water resource pressure of the region in different scenarios according to the standardized index. The method solves the problem of quantification and evaluation of basin water resource pressure under complex conditions.

The present application belongs to the field of urban power system operation and maintenance technology, and discloses a city power system earthquake disaster resilience determination method and system based on multi-dimensional data analysis. The present application obtains the earthquake parameters, power facility information, geographic data and social economic data of each county in the city, and constructs a multi-source heterogeneous evaluation database. Based on the seismic motion parameters and the power facility vulnerability function, the damage probability and the expected loss rate of the function of different voltage level substations and transmission lines are calculated, and the residual function matrix of regional power supply is generated. Combined with the real-time power demand model and the power supply capacity recovery curve, the post-earthquake power supply gap rate is calculated, and the influence of the terrain characteristics on the transmission line repair cost is evaluated to quantify the influence of the earthquake on the economic loss, the affected population and the social stability. The present application can effectively improve the resilience and risk management capability of the power system in the earthquake disaster, and provide technical support for the post-earthquake power rapid recovery and resource optimization allocation.

The invention relates to the technical field of cultural relic protection and public safety, in particular to a cultural relic crime risk early warning method and system fusing space measurement and fuzzy QCA. Cultural relic crime cases, geographic space and social economic data are collected and subjected to standardized preprocessing and double-channel parallel analysis; the quantitative channel analyzes a crime space overflow effect by using a space Durbin model, and generates a hot spot region and an overflow index; a fuzzy QCA model is constructed by a qualitative channel, a high-risk condition combination is identified, a comprehensive risk assessment result is generated by assessing the credibility and situation adaptability of two channel results, a fusion weight is dynamically calculated, a risk level boundary is dynamically determined according to the risk assessment result and an intelligent interval identification algorithm, and optimization and adjustment are performed in combination with a historical early warning effect. According to the method, accurate historical relic crime risk early warning levels and early warning suggestions are output, advantages of space measurement and fuzzy QCA complement each other, the reliability of an early warning result is improved, and powerful support is provided for historical relic protection and public safety.

The invention discloses an environmental risk monitoring and evaluating system and method adaptive to the total factors of the Yellow River basin, and relates to the technical field of environmental monitoring and evaluating, and the system comprises a multi-source data collection module which is used for collecting the ground sensor data and standardized satellite remote sensing data of the Yellow River basin and the social economic data of 9 provinces / regions of the basin; the data preprocessing and cleaning module is used for performing targeted preprocessing and cleaning on the acquired data; the data fusion and analysis module is used for performing multi-dimensional fusion and deep analysis on the preprocessed and cleaned data, mining an environmental risk association rule in combination with a GIS technology, and providing decision support for environmental risk prevention and control of the Yellow River basin; and the environment risk assessment and early warning module is used for performing deep application on the analysis result, and providing Yellow River basin environment risk assessment, accurate early warning and joint defense and joint control decision support by constructing an exclusive index system and optimizing an early warning model and a threshold value. The method is used for monitoring and evaluating the multi-environmental-factor risk of the Yellow River basin.

The application discloses an agricultural field attraction range definition method and system based on an improved breaking point theory, relates to the technical field of agricultural fields, collects multi-source agricultural geographic spatial data and social economic data in a research area, sequentially carries out data cleaning, spatial coordinate matching and attribute standardization processing, and establishes a standardized spatial database; an agricultural field comprehensive quality evaluation index system including four dimensions of agricultural production capacity, infrastructure level, scientific and technological service capacity and ecological environment quality is constructed, the shortest time distance between any two agricultural fields is calculated, and the improved breaking point formula is used to calculate the breaking point position between adjacent agricultural fields, so that the problems of the traditional division result deviating from the regional traffic status and the boundary demarcation not conforming to the actual agricultural service radiation law are effectively solved, the finally determined agricultural field attraction range is more suitable for the practical scene of agricultural product transportation, grass-roots agricultural technology popularization and agricultural convenient service landing, and the division result is more reasonable.

The present application discloses a damage assessment method for nearshore waters, comprising: constructing a three-level relationship network through real-time updating of water quality data and the pollution relationship network of enterprise pollution discharge behaviors, and accurately identifying pollution sources and action chains; the system covers the calculation of direct effect losses, secondary transmission losses and compound interaction losses, and uses ecological model simulation and socio-economic data analysis to comprehensively assess the impact of pollution on the ecosystem and socio-economy; by constructing a dynamic network model, simulating the pollution diffusion and transformation process, and capturing the interactive influence of multiple factors; introducing a dynamic adjustment mechanism, and revising the three-level loss weights in real time according to the change of losses, to improve the accuracy and timeliness of the assessment; the scheme provides a scientific basis for pollution prevention and control and governance, and is of great significance to protecting the ecological environment of nearshore waters and promoting sustainable development.

The invention relates to the technical field of urbanization level evaluation, and particularly discloses an urbanization comprehensive level index optimization method, system and device and a storage medium, and the method comprises the steps: constructing a living standard urbanization index for evaluating the urbanization comprehensive level, determining POI data corresponding to the POI category required for constructing the living standard urbanization index of the target area; according to the social economic data of the target area and the POI data, constructing a living standard index spatial distribution map of the target area; and in combination with the living standard index spatial distribution map, performing normalization processing on the urbanization comprehensive level indexes including the living standard urbanization indexes of the target area to obtain the optimized urbanization comprehensive level indexes of the target area. According to the method, multiple aspects of daily life of residents are covered, construction of an urbanization development index system is perfected, and an important theoretical basis is provided for urbanization level evaluation.

The invention provides a flood control management method based on a social and economic database of a bank flood storage area, and the method comprises the steps: proposing the regional research of social and economic data and underlying surface evolution laws of Middle Beach people in a flood control area; seamless integration and fusion among data such as different actually measured topographic data, high-resolution remote sensing images, flood control engineering design data and social and economic statistical data are realized, a Yangtze river main stream digital scene is constructed, drainage basin underlying surface and row flood storage space social and economic development changes are deduced based on GIS and RS, a row flood storage space database is established, and a flood control system is established. The evolution state of the flood control area is reflected, the Yangtze River main stream flood risk evolution process and driving mechanism can be revealed, and the adaptive flood control treatment method is systematically provided.

The invention discloses a method and a system for evaluating the economic influence of sudden drought on multiple industries, which are used in the technical field of drought disaster loss evaluation, and the method comprises the steps: obtaining soil humidity data and social economic data, and recognizing a sudden drought event in combination with a pre-configured sudden drought definition; calculating an annual average characteristic variable; based on the sudden drought frequency, an annual average exposure degree variable is obtained through a weighted average mode; on the basis of a correlation analysis algorithm and a variance expansion factor analysis algorithm, screening out a characteristic variable and an exposure variable; constructing an interpretable model, and analyzing the characteristic variable and the exposure variable; and quantitatively evaluating the influence of the characteristic variable and the exposure variable on the economic growth of each industry by using a fixed effect regression model, and carrying out robustness test. According to the method, multi-dimensional variables are introduced, the characteristics of sudden drought and the influence of the sudden drought on economy can be captured more comprehensively and accurately, the effect of sudden drought on multi-industry economic growth is quantitatively evaluated, and the result reliability is ensured.

The application discloses a spatial downscaling method and device for regional nitrogen and phosphorus input, an electronic device and a storage medium. The method analyzes nitrogen and phosphorus input, social and economic data and geographic information data at two different resolutions, performs weight evaluation, and calculates high-resolution nitrogen input by using low-resolution nitrogen input data, so as to realize the effect of spatial downscaling. Based on low-resolution nitrogen input data, social and economic data and geographic information data sets, and high-resolution social and economic data and geographic information data sets, the application can predict and evaluate high-resolution nitrogen input, thereby providing a high-precision evaluation method for regional nitrogen and phosphorus management. The application is suitable for regions with social and economic data and geographic information data required for predicting high-resolution nitrogen input data.

The application discloses a kind of water network dike overtopping flood simulation and disaster loss assessment method, belong to the technical field of flood control and disaster mitigation.The method comprises: based on hydrological geographic data, water power analysis is carried out, and potential overtopping area is determined;For potential overtopping area, based on cumulative erosion energy criterion simulation breach evolution, generate breach flow process;According to the breach flow process, simulate flood evolution, generate spatialized disaster intensity field;Combined with disaster intensity field and social and economic data, direct and indirect economic losses are assessed, and comprehensive disaster loss results are generated.The application introduces the physical criterion based on cumulative erosion energy, uses comprehensive intensity index, three-dimensional vulnerability surface and applies graph neural network to simulate cascading failure, solves the problems of missing breach trigger mechanism, single disaster intensity measurement and static disaster loss assessment.

This invention discloses a method for constructing an evaluation model for ecological carrying capacity and industrial layout suitability. By acquiring multi-source ecological environment and socio-economic data of the evaluation area, and constructing three subsystem indicator sets (stress, state, and response) based on the PSR framework, the comprehensive ecological carrying capacity score (ECC) of each evaluation unit is obtained. Industrial layout suitability indicators are extracted from four dimensions: natural suitability, resource support, environmental constraints, and economic accessibility. A combined weighting method using the analytic hierarchy process (AHP) and entropy weighting is employed to calculate the comprehensive industrial layout suitability score (ILS). Finally, the ECC and ILS are quantitatively coupled through a coupling coordination degree model, outputting a coupling coordination degree index D and hierarchical industrial layout decision recommendations. This invention achieves an integrated quantitative evaluation of ecological carrying capacity and industrial layout suitability, providing a scientific decision support tool for regional sustainable development planning.