101 results about "Resource assessment" patented technology

The invention relates to the technical field of terrain wind resource assessment, in particular to a complex terrain wind resource assessment method and system based on CFD enhancement, and the method comprises the steps: processing terrain, weather and vegetation data, and generating a complex terrain feature vector; constructing bidirectional interaction between a mesoscale meteorological mode and computational fluid dynamics, and iteratively optimizing a flow field; fluid dynamic parameters are calculated through reinforcement learning automatic optimization; turbulence simulation is enhanced by combining the generative adversarial network with large eddy simulation; dynamically allocating resolution according to the grid priority of the multi-feature calculation; the lightweight model pre-judges errors, and after the errors reach the standard, evaluation indexes are calculated to complete wind resource evaluation; the system comprises a multi-source data fusion module, a dynamic coupling module, a parameter optimization module, a reinforced turbulence simulation module, an adaptive grid module and an error prediction and evaluation module, and all the modules cooperate to achieve full-process evaluation. The problems that in the prior art, one-way coupling precision is low, manual parameter selection is low in efficiency, turbulence simulation precision and efficiency are difficult to balance, and static grids are wasted are solved.

The invention discloses a marine fishery resource assessment method and system based on buoy sensing monitoring. Firstly, fishery resource change characteristics are analyzed by utilizing historical fishery resource monitoring data of a target sea area, and a monitoring period is determined according to the fishery resource change characteristics; hydrological parameter change data are obtained, and a hydrodynamic simulation model is established; an initial buoy sensing monitoring array is constructed by combining the effective monitoring range of sonar monitoring buoys; the array is imported into a hydrodynamic simulation model, and node displacement change information in a monitoring period is obtained; and finally, the buoy monitoring array is optimized according to a displacement change result, an optimized monitoring layout scheme is formed, and dynamic monitoring and scientific evaluation of the fishery resources in the target sea area are realized accordingly. According to the method, the rationality and monitoring precision of buoy layout can be improved, the hydrodynamic environment influence and the resource change rule are considered, and technical support is provided for sustainable development and management of marine fishery resources.

The invention relates to the technical field of wind energy resource assessment, and discloses a wind resource assessment method based on a millimeter wave wind finding radar. The method comprises the steps of collecting wind field data of a target area through a millimeter wave wind measurement radar and performing preprocessing to generate a standardized data set; inputting the data into a prediction model to obtain a wind energy distribution characteristic graph; generating a parameter set by adopting threshold segmentation based on the feature map, and dynamically constructing an evaluation function for simulation evaluation; synchronously collecting actual wind energy data, and calculating a deviation matrix between the actual wind energy data and a predicted value to quantify an evaluation error; performing parameter correction on the prediction model by using the error to obtain an optimized model; and finally, regenerating a feature map by adopting the optimization model and completing resource evaluation. According to the method, through online model correction and dynamic evaluation function construction, closed-loop optimization and data driving in the evaluation process are realized, and the accuracy of an evaluation result and the adaptability to a specific site are improved.

The invention discloses a geothermal resource assessment method and system based on big data analysis, and is applied to the technical field of digital analysis. The method comprises the following steps of obtaining multi-source heterogeneous data of historical drilling engineering, performing data preprocessing and feature engineering, and establishing a drilling success probability intelligent prediction-risk quantification model; in combination with geospatial information and environmental multi-source data, identifying an earth surface thermal anomaly region as a target region to perform geothermal potential assessment, and completing preliminary grading assessment of the target region; integrating seismic active band high-frequency monitoring data, inverting deep structure features by using a seismic wave velocity tomography technology, and performing multi-mode correlation matching with a target region; the coupling model realizes accurate evaluation and grading screening of a target region; and constructing a geothermal target area digital twinborn model fused with geologic and geophysical constraints, and realizing dynamic evaluation and productivity prediction of geothermal resources. Automatic geothermal resource evaluation is achieved, and efficient development and reasonable utilization of geothermal resources are promoted.

The invention relates to a fish body detection counting method for a channel behind a fish pump of a fishing boat, and provides an NMS-free fish body detection model MGI-RTDETR based on an improved RT-DETR for small targets, rapid movement, strong blur, highlight shielding and limited shipborne computing power. The model integrates multi-scale grouping interaction, dynamic context mixing, detail fidelity fusion, deployment period re-parameterization and back projection up-sampling, and real-time detection of one fish and one frame is achieved. And in combination with lightweight multi-target tracking, outputting paragraph counting by adopting a one-way cross-line combined de-duplication strategy. According to the method, missing detection and time delay can be remarkably reduced, edge deployment is facilitated, and the method is suitable for near-real-time fishing estimation, operation monitoring and resource evaluation.

The invention relates to the technical field of clean room full-process intelligent management, and discloses a clean project full-life-cycle intelligent management digital twin platform, which comprises a full-cycle data center module, a virtual-real bidirectional interaction engine module, a full-cycle management module and a multi-terminal collaborative interaction module which are connected with one another, the whole life cycle of design, construction, operation and maintenance and decommissioning is covered, whole-course tracing of design-construction-operation-decommissioning is achieved, closed-loop interaction of virtual model rehearsal and entity execution feedback is constructed, and an intelligent decision function is constructed to cover the whole process. Comprising performance rehearsal in a design stage, progress management and control in a construction stage, deep optimization in an operation and maintenance stage and resource evaluation in a decommissioning stage. Through deep fusion of the dynamic BIM model and multi-stage multi-source data, virtual-real two-way interaction and full-period intelligent management, the method is suitable for full-process collaborative management of clean environments such as semiconductors, biological medicines and foods, and full-stage precise management and control from early planning to final decommissioning are realized.

This application discloses a comprehensive assessment method and system for multi-source data management and correction of watershed fish resources. The method includes: extracting multi-dimensional features from a first data matrix to obtain a first feature matrix; classifying species data based on anomaly scores, outputting verification results, and correcting the first feature matrix to obtain a second feature matrix; acquiring environmental DNA sequencing data and corresponding environmental data; obtaining a first eDNA dataset from the environmental DNA sequencing data through ecological screening; correcting the species in the first eDNA dataset to obtain a second eDNA dataset; fusing the second eDNA dataset with the second feature matrix; calculating biodiversity indices and analyzing community structure; analyzing long-term trends in population and community structure; and generating a comprehensive assessment report. This application achieves full-process automation and intelligence from data quality control and fusion to assessment, significantly improving the accuracy and efficiency of watershed fish resource assessment.

This invention provides a method and agent-based approach for identifying and scheduling computing resource requirements, relating to the field of cloud computing resource management technology. The method includes: receiving a user's fuzzy description of computing resource requirements; parsing the user's requirements using natural language processing (NLP) technology to identify user intent and key entities; proactively guiding the user to complete missing parameters through multi-turn dialogue based on key entities and a built-in knowledge base; calling a resource evaluation model to quantify the parameters and generate a list of computing resource requirements; obtaining a set of candidate resources that meet the list of requirements; calculating multi-dimensional utility scores for each candidate resource; generating multiple recommendation schemes based on different weighting strategies across multiple dimensions, and generating natural language descriptions of recommendation reasons for each scheme; and executing resource allocation based on the user's selection. This invention improves resource matching accuracy and scheduling efficiency by accurately understanding and quantifying the user's computing resource requirements through an agent, thereby generating a computing resource scheduling scheme.

The invention provides a smart tourism online comprehensive management system, belongs to the technical field of tourism data management, and can make tourism resource assessment more accurate. Static attributes and dynamic indexes are integrated by means of a regional industry knowledge graph, a unified data support network is constructed, a plurality of Pareto optimal routes are generated in combination with a multi-objective optimization algorithm, and personalized requirements of tourists on time, cost, interest matching degree and experience credibility are met; route adjustment can be carried out according to tourist real-time states, resource dynamic states and macroscopic passenger flow early warning automatic or response intention changes in the journey, and journey dynamic optimization is achieved; and meanwhile, passenger flow can be predicted through a graph neural network model, a risk early warning and multi-subject collaborative scheduling scheme can be generated, regional tourism collaborative management is assisted, the problems that a traditional system is large in recommendation deviation, cannot dynamically adapt and is insufficient in collaborative scheduling are effectively solved, and tourism experience of tourists and regional tourism service quality are remarkably improved.

This application relates to the field of intelligent aerospace technology and discloses a satellite autonomy method driven by embodied intelligent agents, applicable to subsatellites belonging to an in-orbit constellation. It constructs a multi-agent framework comprising multiple autonomous intelligent agents, including at least a resource assessment agent and a resource optimization agent. In response to a resource assessment command regarding the target mission, the method acquires the subsatellite's in-orbit operating parameters. The resource assessment agent is invoked to perform resource assessment based on the in-orbit operating parameters, obtaining the mission resource assessment result, which is then fed back to the in-orbit constellation. If mission feasibility indicates that the subsatellite can execute the target mission, the method acquires a single-satellite mission plan fed back by the in-orbit constellation. The resource optimization agent is invoked to optimize resource allocation based on the single-satellite mission plan, obtaining a mission operation plan. Its beneficial effects are that it improves the intelligence level of subsatellites in remote sensing observation missions and enhances the satellite's in-orbit autonomy.

This invention belongs to the interdisciplinary field of artificial intelligence and geological resource assessment, specifically relating to a method and system for predicting the energy storage potential of salt caverns based on multi-source geological information. It aims to address the problems of low prediction accuracy and difficulty in balancing breadth and precision in existing technologies due to single-source data, static models, and lack of adaptive capabilities. The method includes: acquiring multi-source data such as seismic, well logging, core, and geostress data; constructing a geological feature fusion vector containing seven core parameters; establishing a high-dimensional nonlinear mapping model driven by a deep neural network; dynamically adjusting the prediction range based on data coverage density and confidence level; and achieving continuous model iteration through online incremental learning. The system integrates data quality assessment, anomaly handling, and distributed computing modules. By adopting the above technical solutions, this application can achieve a significant improvement in prediction accuracy and adaptive intelligent adjustment of the prediction range.

The invention discloses a method for rapidly generating a flat ground full-excavation slope ramp, and belongs to the technical field of strip mine mining. Comprising the steps of collecting topographic data of a mining area and data of a slope crest line and a slope bottom line, and generating a visual three-dimensional mining area map model; determining a ramp line and a mining auxiliary line of a mining area in the three-dimensional model; and calculating the coal rock content according to the stripping model. According to the method, design requirements can be quickly responded, and the design period is remarkably shortened; through accurate calculation and optimization, the generated slope ramp scheme is more reasonable, and the transportation distance and energy consumption can be effectively reduced; the method has high adaptability and can flexibly deal with mining scenes under complex geological conditions. In addition, the method can accurately determine the volume and the coal rock content of the stripped ore body, and provides reliable data support for resource evaluation and mining planning.

This invention relates to the field of marine resource assessment technology, and particularly to a method and apparatus for refined assessment of marine wave energy resources. The method includes: acquiring wind field data, water depth and topography data, and boundary wave data of the target sea area to be analyzed; constructing a nested grid wave numerical model; based on the wave numerical model, obtaining wave elements for each moment within at least one complete climatic year, including significant wave height and wave period; based on the wave elements of the inner and outer grids, obtaining the target wave energy flux density corresponding to each inner grid; and based on the target wave energy flux density, obtaining the resource utilization rate, average wave energy flux density, significant wave occurrence frequency, and resource stability of each inner grid in the target sea area, thereby conducting a refined assessment of the wave energy resources of each inner grid in the target sea area. The above technical solution enables a refined assessment of wave energy resources in the target sea area, providing technical support for wave energy development.

This invention discloses a PCB layout evaluation method, system, and medium that integrates layout optimization and resource assessment; it relates to the field of electronic design automation technology; this solution is based on PCB layout design, layout resource assessment, and layout quality assessment; it combines the minimum area constraints of different component spacing constraints to place components on the PCB board, and analyzes and evaluates the actual effective area on the PCB board to reflect the effective utilization of the PCB board, assisting engineers in predicting the PCB layout design resource situation in advance, facilitating the optimization of PCB board utilization, thereby reducing PCB raw material costs and manufacturing costs; after the layout is completed, the layout is evaluated from the overall layout to the local layout, providing guidance for the optimization of the layout results and improving the quality and reliability of PCB layout design.

The invention relates to the technical field of database information management, discloses a big language model driven ODS layer full-process data resource evaluation modeling system, method and device, a storage medium and a program product, and is used for solving the technical problems of low modeling efficiency and poor effect in the prior art. Comprising a data input module used for capturing a table structure and table metadata of a newly-added business table corresponding to a target iteration version in real time; the modeling evaluation module is used for calling a large language model to fuse historical evaluation records and resource classification rules, evaluating data resources contained in the newly-added service table and outputting a resource classification result and a modeling evaluation conclusion; the data modeling module is used for calling a large language model to generate field description for each field contained in the newly added business table when modeling needs to be executed, and analyzing business source codes related to enumeration fields to generate field description of the enumeration fields when the fields are enumeration fields; and based on the table structure, the table metadata and the field description, generating a data resource model on the ODS layer.

The invention relates to a Dabie mountain sustainability research method, which constructs a three-dimensional collaborative system by integrating natural resources, cultural values and market demands, and realizes dynamic balance of ecological protection and economic values. The method is mainly characterized by comprising a resource evaluation model, an ecological monitoring system and an industrial symbiosis network, and is suitable for sustainable development planning of an ecological sensitive area.

This invention discloses an artificial intelligence-based method, device, and medium for scheduling computing resources, relating to the field of computing resource scheduling technology. The method includes: inputting a vector alignment table into a resource evaluation deep neural network to calculate resource suitability scores and conflict risk scores; performing candidate resource clustering and lower limit constraint verification through a scheduling optimization strategy to generate a candidate resource list; setting the resource suitability scores and conflict risk scores in the candidate resource list as sorting keys, performing fine-grained ranking within clusters, selecting head resources for distribution, and collecting acceptance receipts, initiation receipts, and operation telemetry receipts to generate a feedback packet; inputting the feedback packet into a feedback learning deep neural network to perform behavior replay comparison, locating key conflict points, dynamically updating the scheduling optimization strategy, and registering weight migration trajectories to generate a computing resource scheduling record set. This invention achieves continuous optimization of the scheduling strategy, improving the decision-making accuracy and operational stability when facing dynamic loads.

The invention discloses a maritime emergency search and rescue resource assessment and responsibility allocation method. The method comprises the following steps: constructing a maritime emergency resource allocation risk assessment model, and constructing a maritime emergency search and rescue difficulty analysis and assessment model; constructing a responsibility subject allocation index system based on a maritime emergency search and rescue resource allocation risk assessment result and a search and rescue difficulty assessment result; establishing a multi-objective optimization model by minimizing the response time, maximizing the resource utilization rate and optimizing the load balancing and responsibility subject allocation index system; an NSGA-III algorithm is adopted to solve the multi-objective optimization model, and a Pareto optimal solution set is obtained; and performing cooperative game screening on an optimal solution in a Pareto optimal solution set based on responsibility allocation calculation of a dynamic Shapley value and a contract network protocol mechanism, generating a final task-rescue station responsibility allocation matrix, and realizing dynamic cooperative decision-making of a responsibility subject.

The invention provides a cloud computing resource scheduling method and device, equipment, a medium and a program product, and relates to the technical field of cloud computing, and the method comprises the steps: obtaining cloud resource pool state data, carrying out the quantitative evaluation of the resource imbalance state of a cloud resource pool through a cloud resource evaluation model based on the cloud resource pool state data, and obtaining the resource imbalance state of the cloud resource pool. Outputting a resource imbalance quantification result, wherein parameters of the cloud resource evaluation model comprise a resource utilization rate, a resource deviation rate, a host fragment rate, a host allocation rate and a resource utilization rate balance degree; abstracting resource related indexes of a host machine in the cloud resource pool state data into a resource vector group, and abstracting demand related indexes of a virtual machine in the original index data into a demand vector group; taking a resource imbalance quantization result as an optimization direction, and performing iterative optimization clustering on the association relationship between the demand vector group and the resource vector group by adopting a clustering algorithm of a Pearson's correlation coefficient to obtain a target association relationship; and executing resource optimization scheduling based on the target association relationship.

The invention relates to the technical field of data management, and discloses a fishery resource evaluation method and system, and the method comprises the steps: extracting multi-source fishery data and a ship trajectory set of a target drainage basin, and obtaining an original feature set after processing; decomposing the original feature set into orthogonal waveform components and waveform coefficients according to the spatial distribution of the target watershed; performing linear superposition on the basis vectors of the orthogonal waveform components based on the waveform coefficient to obtain a data coverage density field; sorting the density values in the data coverage density field, and dividing a density value interval of the target drainage basin; according to the density value interval, a field value in the data coverage density field corresponds to a reliability level, and a space reliability distribution map is obtained; mapping ship behavior characteristics in the ship trajectory set to a spatial reliability distribution map to obtain an evaluation sequence of the target drainage basin; the efficiency of multi-source data integration and feature extraction in the fishery resource evaluation process can be improved.

This invention proposes a data analysis-based method and system for assessing fish resources in reservoirs, belonging to the field of resource assessment. The method includes collecting ecological characteristic data and population characteristic parameters of introduced and native fish populations in the reservoir; calculating niche overlap indices between introduced and native fish populations in both spatial and trophic dimensions, and integrating these to obtain a comprehensive niche difference index; calculating the population growth potential of each population and obtaining a fitness difference index; processing the comprehensive niche difference index and fitness difference index to obtain a coexistence stability score and determining the coexistence stability level of the two populations; acquiring time-series data of the niche overlap index, extracting fluctuation characteristic parameters, and generating a fish resource assessment report based on the fluctuation characteristic parameters and the coexistence stability level. This invention can comprehensively assess niche differences between populations.

The invention belongs to the technical field of deep-sea polymetallic nodules, particularly relates to an image-based deep-sea polymetallic nodule identification and reserve evaluation method and system, and aims to solve the problems of brightness imbalance, nodule shape scale variability and the like generally existing in deep-sea nodule pictures. According to the method, transform and a convolutional neural network are combined, global background consistency and local fine granularity retention are considered, and cross-layer circulation of multi-scale tuberculosis information is realized through long and short distance combined jump connection, so that the tuberculosis segmentation performance in a complex deep sea scene is improved. Based on the segmentation result, the actual sampling data is further combined to realize reserve evaluation, and reliable technical support is provided for deep sea polymetallic nodule resource evaluation.

The invention discloses a fusion calculation method of a quantum classical hybrid calculation system and a related device, and the method comprises the steps: carrying out the splitting processing of a task request applied by the quantum classical hybrid calculation system, so as to obtain calculation subtasks independently completed by quantum calculation, classical calculation and intelligent calculation; in response to the split calculation sub-task type, configuring the heterogeneous calculation resources to the corresponding calculation sub-tasks; the heterogeneous computing resources comprise quantum computing resources, classical computing resources and intelligent computing resources; the computing resources are evaluated and analyzed according to the resource evaluation and intelligent analysis module to obtain a corresponding scheduling decision basis; inserting the calculation subtasks into the corresponding task queues, and scheduling the task queues based on the scheduling decision basis, the user-defined scheduling strategy and the first linkage relationship of the calculation subtasks; according to the method, a classical and efficient fusion calculation technical scheme of quantum is provided, and an efficient solution is provided for a complex calculation problem through computing power complementation.

The invention relates to the technical field of wind energy resource assessment, and discloses a wind power plant wind energy resource assessment method and system, and the method comprises the steps: obtaining a wind speed monitoring value sequence of wind speed monitoring values of a target wind power plant in a target time period, and a barometric pressure value sequence of barometric pressure values in the target time period; calculating a wind energy resource evaluation factor corresponding to the target wind power plant at the first target moment based on the wind speed monitoring value sequence and the atmospheric pressure value sequence; determining wind energy resource evaluation factors corresponding to the remaining target moments, and calculating a wind energy resource evaluation metric value of the target wind power plant according to all the wind energy resource evaluation factors; according to the relation between the wind energy resource assessment metric value and the preset wind energy resource assessment metric value, whether the target wind power plant meets the power generation condition or not is judged, the relevance and fluctuation change characteristics of the wind energy resources can be quantitatively analyzed, and the assessment precision and the assessment reliability of the wind energy resources are guaranteed; and technical support is provided for scientific planning and efficient operation of the wind power plant.

The invention relates to the field of fishery data fusion, and discloses an offshore fishery data resource assessment method combined with multi-source heterogeneous data fusion, which comprises the following steps of: performing data preprocessing, data space-time matching and data heterogeneous fusion on offshore fishery related multi-source data to obtain fused offshore fishery related data; and carrying out data analysis on the fused offshore fishery related data, and evaluating resource states of different positions in a sea area by combining a fishery resource evaluation model so as to realize early warning of offshore fishery data resources. According to the method, excessive fishing, population structure degradation and ecological chain collapse can be avoided, and overall management of related resource data of Xian'an offshore fishery in different dimensions is realized.

This application provides a planning method for a resource-saving, low-carbon data industrial park, relating to the fields of renewable energy and energy conservation technology. The method includes: acquiring a set of environmental parameters for a target area and processing the set of environmental parameters; constructing a regional resource assessment model based on the processed environmental parameter set to integrate multiple energy potential parameters and their interactions, thereby outputting dynamic resource assessment results; constructing a site selection planning evaluation system based on the resource assessment results and pre-set park construction demand constraints; and optimizing the indicator weights in the site selection planning evaluation system through a dynamic weight adjustment mechanism, according to the temporal variation pattern of the interactions, to generate an optimized site selection planning scheme.

The invention discloses an intelligent matching platform for community health resources and home-based care demands, and relates to the technical field of intelligent matching of care services and health resources. The data acquisition module acquires multiple items of data related to community health resources and home-based care demands in real time, performs data preprocessing after acquisition, and transmits the data to the resource and demand analysis and evaluation module; according to the method, comprehensive and real-time multi-source data perception is realized by deploying multiple types of sensors and a multi-source data acquisition interface, accurate quantification and characterization of home-based care requirements and community health resources can be carried out, and a K-Means clustering algorithm and an Apriori association rule mining algorithm are adopted to fully analyze the relationship between the requirements and the resources, so that the accuracy and the reliability of the home-based care requirements and the community health resources are improved. A multi-dimensional resource evaluation index system is established, and an analytic hierarchy process (AHP) is adopted to calculate a resource evaluation index.

The application discloses a marine economic fish resource evaluation platform based on multi-source data fusion. The platform sets a target water area layer and multi-period monitoring, uses a sonar detection device to collect data to generate first fish school characteristics, collects images through an underwater camera device and generates second fish school characteristics through a preset image recognition model; a fish school characteristic matrix is constructed based on time window analysis, noise time periods are screened by using matrix similarity discrimination; the recognition process of the noise image set is dynamically adjusted in edge segmentation parameters, and the resource evaluation of economic fish is carried out by fusing and correcting the recognition result. Through multi-source data fusion analysis, difference comparison of fish school characteristics and dynamic image parameter adjustment, the application effectively improves the comprehensiveness, reliability and accuracy of fish school characteristic evaluation in complex water environment, can provide real-time dynamic data support for fishery resource management and marine ecological protection, and has a wide application prospect.

The invention relates to the technical field of offshore wind resource assessment, and discloses a fan missing wind speed restoration method, which comprises the following steps: acquiring adjacent wind speed characteristics of missing wind speed of a target fan and historical wind speed characteristics of adjacent fans; predicting a wind speed prediction value of the missing wind speed based on the adjacent wind speed features and the historical wind speed features; estimating a wind speed correction value of the missing wind speed according to the historical working power and historical wind speed characteristics of the adjacent fans; and performing weighted fusion calculation on the wind speed prediction value and the wind speed correction value to obtain a missing wind speed, and repairing the target fan according to the missing wind speed. According to the method, multi-dimensional prediction of the missing wind speed is achieved by fusing the time sequence wind speed characteristics of the target wind turbine and the space correlation characteristics of the adjacent wind turbines, a physical correction mechanism based on the relation between historical power and the wind speed is introduced, the predicted value is corrected by using the strong physical correlation parameter of the working power of the wind turbines, and the prediction accuracy of the wind turbines is improved. And the precision and the reliability in repairing the missing wind speed are improved.

The invention discloses a cross-regional land market information analysis and price prediction method based on federated learning, and relates to the technical field of land resource assessment, and the method comprises the following steps: obtaining crop-soil coupling data and a land ecological connection matrix of a target object; performing topological mapping on the crop-soil coupling data according to the land ecology connection matrix, and performing mutual projection on a topological mapping result and the crop-soil coupling data to generate a tensor projection result; and performing time sequence matching on the crop-soil coupling data and the tensor projection result, and performing lag expansion on a time sequence matching result by applying an adaptive attenuation kernel to generate a time sequence rotation result. According to the scheme, attenuation parameters can be automatically optimized according to local data characteristics through the dynamically adjusted adaptive attenuation kernel, meanwhile, a tensor correction factor is introduced to eliminate cross-data-source mapping errors, and value fluctuation rules of different ecological region lands in a crop rotation period can be accurately captured.