1270 results about "Information data" patented technology

The invention relates to the technical field of management and control systems, in particular to a digital intelligence system applied to collaborative management and control of water-power engineering construction participating units, which comprises a project data management module covering water-power engineering construction full life cycle management, extracting multi-source information data from various subsystems, and constructing a project view and a project management information base; the project risk analysis module is used for constructing an intelligent risk analysis model for risk analysis and generating a dynamic evaluation result, a graded early warning notification and an auxiliary decision scheme; the project collaborative management module is used for processing graded early warning notification and auxiliary decision-making schemes by using a multi-layer perceptron model, and generating finalizing service achievements and management process records; and the project document management module is used for performing compliance automatic checking and processing on the electronic documents needing to be archived, and dynamically updating and optimizing the project management information base. Through the closed-loop management and control system, the cooperative management and control efficiency of water-power engineering construction participation units is improved.

The invention relates to the technical field of material verification management, and discloses a government affair material intelligent verification method and system based on machine learning, and the method comprises the steps: obtaining the text information data and verification rules of historical materials; multi-modal feature extraction is carried out; establishing a dynamic verification rule knowledge graph, and verifying the multi-modal features and the target feature points of the text segments to generate a primary verification strategy; performing deep verification processing on the material text fragment to generate a secondary verification strategy; performing third-time verification on the material text fragment subjected to the second-time verification by triggering cross-page feature matching to realize cross-page text fragment association and multi-modal feature fitting so as to generate a third-time verification strategy; performing iterative comparison on the results of the three rounds of verification to generate a credibility score; and the comparison result is adjusted according to the credibility score in combination with the verification risk abnormity assessment, so that a final verification decision strategy can be obtained, and efficient, accurate, dynamic and comprehensive intelligent verification can be realized.

The invention discloses an intelligent building construction operation management method based on big data, and belongs to the technical field of building construction management. Comprising the following steps: step 1, real-time data acquisition of construction site personnel, equipment and environment is realized, and a dynamic information database is established; 2, preprocessing and feature extraction are carried out on the collected multi-source heterogeneous data, and fusion and intelligent analysis of real-time data are achieved; step 3, accurately identifying risk factors and implementing refined early warning and intelligent intervention aiming at a single risk; 4, construction resource configuration is dynamically optimized, the resource utilization efficiency is improved, and meanwhile the cost and the safety risk are reduced; step 5, constructing a block chain data sharing mechanism, and realizing data tracing and intelligent management of a construction full life cycle; and step 6, forming a self-adaptive closed-loop feedback mechanism, and promoting intelligent transformation of construction management from passive response to active prediction.

The invention provides an intelligent boxing method and system. The intelligent boxing method comprises the steps of obtaining boxing task information and generating a boxing scheme. The boxing task information comprises the size, the weight, the stacking limitation, the number and the priority of each cargo, and the size, the bearing capacity and the occupation state of each loading unit. And under the condition that the size, bearing and stacking constraint conditions are met, a plurality of candidate boxing combinations are generated, the loading utilization rate, the residual space distribution and the shape matching degree are evaluated based on a preset optimization target, and an optimal scheme is selected. The system comprises an input terminal, a task information receiving module, a data storage module, a task and scheme storage module, an operation processing module and a final boxing scheme generation module. According to the method, multi-dimensional constraint matching and weight balance are considered, and space waste and transportation risks are avoided; the maximum greedy algorithm and the adaptive large neighborhood search optimization are combined to realize the combination of automation and experience. The method can be expanded to batch task scheduling and grouping sequencing, so that the calculation complexity is reduced, and the overall boxing and transportation efficiency is improved.

The invention relates to the technical field of smart city data visualization, in particular to a visual smart city display method, which comprises the following steps: S1, collecting traffic flow data, energy consumption data, environment monitoring data and city three-dimensional geographic information data in real time; s2, constructing a reference three-dimensional model with a space coordinate system; s3, mapping the data into a dynamic data layer with a timestamp; s4, superposing the dynamic data layer to the reference three-dimensional model according to space-time coordinates to generate a fused dynamic scene; s5, receiving deduction parameters input by a user, and calculating a corresponding evolution path in real time; and S6, converting the evolution path into a dynamic visualization effect, and outputting the dynamic visualization effect to a display terminal. According to the invention, through integrated processing of multi-source dynamic data fusion, space-time path deduction and visual output, continuous expression and dynamic evolution display of the operation state of the smart city are realized.

The invention discloses a ship desulfurization system reliability evaluation method and system based on multi-source information fusion, and the method comprises the steps: collecting multi-source information data of a hybrid desulfurization system, and carrying out the self-adaptive preprocessing; generating a fusion feature vector; constructing a dynamic Bayesian network based on multi-source fusion features, performing real-time reasoning by adopting data-driven transition probability learning and particle filtering, describing transient behaviors of system state evolution and mode switching, and performing dynamic multi-state reliability modeling; a fault mode is automatically extracted, and data-driven systematic risks are identified and quantitatively analyzed; a multi-resolution digital twinborn architecture is constructed, dynamic simulation prediction is carried out, a self-adaptive updating mechanism is adopted to keep the model synchronous with a physical system, and a virtual verification environment for reliability evaluation is provided; according to the method, an intelligent decision optimization system is constructed, self-adaptive generation and dynamic adjustment of a maintenance strategy are realized, closed-loop feedback is carried out, and the accuracy of reliability evaluation of the hybrid desulfurization system is improved.

The invention discloses a new energy automobile hybrid power system cooperative control device and method.The new energy automobile hybrid power system cooperative control device comprises a multi-source data collection module, a cooperative control center and an execution unit, and the multi-source data collection module transmits collected information data to the cooperative control center; the cooperative control center comprises a data fusion unit, an energy management module, a heat management module and a cooperative decision-making unit, the data fusion unit receives data information of the multi-source data acquisition module, carries out fusion processing, and transmits the data information to the energy management module and the heat management module; the energy management module and the heat management module output a control strategy to the collaborative decision-making unit, and the collaborative decision-making unit judges a correction strategy and then sends a control instruction to the execution unit. The method has the advantages that cooperative control of energy management and heat management is achieved, various dimension data of road conditions, driving behaviors, power states and heat source states are fused, the problem of system unbalance caused by single module optimization is solved, and dynamic cooperation of energy management and heat management is achieved.

The present disclosure describes methods, systems, apparatus, and media for object identification and classification, utilizing multi-feature and multi-modal data. This includes shape, material, brand, price, odor, taste, tactility, and sound. The system integrates a server space for data processing, a querying device for iterative searches, and a data interface module for refining results. It features AI-driven image optimization, feature extraction, and pattern recognition, employing novel techniques for fusing multi-feature and multi-modal embeddings utilizing multi-head attention. Additionally, a linker module powered by two active learning with feedback loops AI models consolidates scattered data into a unified object information database. The system also employs novel AI algorithms for isolating the object of interest through a saliency map and semantic analysis, as well as for enhancing raw images with a GAN-autoencoder.

The invention discloses a multi-agent collaborative scheduling method and system oriented to science and technology intelligence analysis, and relates to the technical field of science and technology intelligence analysis, and the method comprises the steps that a task issuing layer outputs a standardized task description by executing task demand element analysis; after the intelligent coordinated scheduling layer receives the standardized task description, closed-loop collaborative decision making is carried out, and a task distribution instruction is output; and the professional agent execution layer drives the data acquisition agent group to acquire science and technology information data through a data access adapter of the data resource layer, executes a science and technology information analysis task, outputs a structured processing result, and visually displays the structured processing result to a user through the task release layer. The technical problem that in the prior art, a science and technology information processing system lacks intelligent task allocation, and consequently the information processing efficiency is low is solved, and the technical effects that four-layer architecture closed-loop cooperation of science and technology information analysis tasks and efficient dispatching of specialized intelligent agent groups are achieved, and the task allocation accuracy and the information processing efficiency are improved are achieved.

The invention discloses a micro-report generation method and device and a storage medium, and relates to the technical field of data processing, and the micro-report generation method comprises the steps that a natural language question input by a user is received, the natural language question is matched with a preset question example library, and a target question example is determined; obtaining a business index in the natural language question, and determining a data model corresponding to the business index; based on the target problem example, the business index and the data model, generating a calculation semantic configuration; generating a target SQL query by combining the corresponding model information, the data source information and the authority control rule based on the calculation semantic configuration; and generating the micro-report by executing the target SQL query. According to the method, the target question example is determined by matching the natural language question with the preset question library, and the semantic configuration is dynamically generated and calculated in combination with the specific business index and the data model, so that the target SQL query is generated, and the effect of immediately responding to the dynamic query according to the natural language question is achieved.

The invention discloses a broadcast television network security operation method and system based on a large model, and the method comprises the steps: collecting log, network flow and terminal behavior data in real time, storing the data in a Kafka message queue, receiving the data through an AI intelligent noise reduction module, extracting alarm text semantic features through an XLM-ROBERTa model, and carrying out the noise filtering through combining with a multi-classification model, thereby obtaining high-value data; inputting the high-value data and security document knowledge corresponding to the network threat intelligence into an RAG knowledge base module, generating enhanced context information data through knowledge extraction, vectorization storage and similarity retrieval, inputting the enhanced context information data into a cue word of a reply model, and outputting a first threat analysis reply; inputting the high-value data and the first threat analysis reply into a multi-model MOE architecture, distributing tasks through a gating network, integrating expert network output results, and generating a second threat analysis reply and a corresponding attack thermodynamic diagram; and executing feedback optimization operation of the corresponding module based on the second threat analysis reply, thereby improving the safety operation efficiency of the broadcast television network.

The invention provides an intelligent mine open-pit coal mine measurement system and method, and relates to the technical field of coal mines, and the system comprises a browsing module which is used for obtaining coal mine information data of an open-pit coal mine, and carrying out the multi-window linkage display of the coal mine information data; the measurement module is used for measuring coal mine parameters of the open pit coal mine according to the coal mine information data to obtain target measurement data; the modeling module is used for performing three-dimensional modeling processing on the open pit coal mine based on the coal mine information data and the target measurement data to obtain topographic data; and the management module is used for carrying out data management and automatic coordinate conversion on the topographic data, and carrying out data level-to-level management and data security control according to a preset authority level. Compared with the prior art, according to the embodiment of the invention, through a unified data acquisition and data measurement mode, automatic nesting of the orthoimage data, the laser point cloud data, the image data and the topographic data is realized, and the measurement efficiency and accuracy of the open-pit coal mine are improved.

The invention discloses a WebSocket-based instant message task assigning system. The system comprises two parts, i.e., a server and clients, wherein the server is deployed on an application server and configured with ports for providing external services, and the server is then started; the clients comprises an APP client and a PC client; and information data transmission among the server, the APP client and the PC client is achieved based on the WebSocket protocol, that is, the server provides the instant messaging service, and the clients achieve acquisition of data from the server. Compared with the prior art, the system provided by the invention has the advantages that WebSocket-based instant message task assigning is achieved, and information can be synchronized between the information acquisition clients, so that high timeliness, effectiveness and safety of the information are ensured.

The invention relates to the technical field of artificial intelligence and data processing, in particular to a policy and enterprise intelligent matching method and system based on deep semantic understanding. The method comprises the following steps: acquiring multi-source policy information data and enterprise information; generating an enterprise multi-dimensional portrait according to the enterprise information; performing first matching and second matching on the multi-source policy information data and the enterprise multi-dimensional portrait respectively; and constructing a comprehensive matching model, and based on the first matching result and the second matching result, using the comprehensive matching model to complete policy and enterprise intelligent matching. According to the policy and enterprise matching method, the problems of low efficiency, inaccurate matching and important information omission in a traditional policy and enterprise matching method are solved through matching policies and enterprise portraits. Through automatic data collection, preprocessing and matching calculation, manual intervention is greatly reduced, the policy and enterprise matching efficiency is improved, and an enterprise can quickly find a policy suitable for the enterprise.

The invention discloses a commodity traceability method and system based on a block chain. The method comprises the following steps: acquiring basic information data of a commodity to generate a unique identifier of the commodity, and constructing a distributed account book in combination with a transaction hash value and an operation timestamp; constructing a commodity propagation ecological map by using a graph database technology based on a distributed account book; aggregating the full-node circulation data, and performing standardization processing to form a cross-platform integrated data set to obtain commodity propagation path data; analyzing to obtain transaction data of the commodity propagation path data, and dynamically adjusting graph node weights; and finally, performing anomaly detection and block chain verification on the updated commodity propagation ecological map to generate a commodity traceability report. The problem that in a complex propagation network, it is difficult to ensure the credibility of a commodity data source and achieve cross-system efficient integration is solved, and the effects of improving the transparency and authenticity of supply chain data, optimizing the commodity traceability efficiency and guaranteeing the transaction credibility are achieved.

The invention relates to the technical field of Internet of Things, and discloses a remote diagnosis system and method for a complex system in an Internet of Things environment, and the system comprises a data collection module which is used for collecting the operation state information of the complex system; the data transmission module is used for transmitting the running state information to the cloud processing center; the cloud processing center is used for performing fault analysis according to the received operation state information based on a machine learning algorithm, generating a fault diagnosis result and a corresponding maintenance suggestion and transmitting the fault diagnosis result and the corresponding maintenance suggestion to the user terminal; and the user terminal is used for receiving the fault diagnosis result and the maintenance suggestion, remotely accessing the system state report of the complex system and remotely controlling the complex system. According to the invention, efficient remote monitoring, accurate fault diagnosis and real-time maintenance guidance of the complex system in the Internet of Things environment can be realized, the maintenance cost is reduced while the maintenance efficiency is improved, and thus the maintainability and safety of the complex system are enhanced.

According to the multi-source information fusion robot positioning method and system for the unstructured environment provided by the invention, fusion processing is carried out on multi-source information data such as laser point cloud, environment image information and acceleration which are acquired in real time, so that the multi-source information fusion robot positioning method and system for the unstructured environment can be realized in a severe weather state and a dynamic unstructured environment. Carrying out high-robustness real-time positioning under the condition of violent illumination change; in a geometrically degraded roadway area, registration positioning of laser point cloud emission fails due to lack of enough external characteristics, and at the moment, the visual positioning module can still work normally and complete robot repositioning by detecting matched image information; in an environment lacking enough illumination, the laser point cloud and acceleration information can still provide enough positioning fusion data input for the computing unit.

The invention belongs to the technical field of information and communication, and relates to an active user detection and data decoding method of an asynchronous massive machine type communication system. Aiming at the problem that the detection and estimation performance is reduced due to unknown user time delay in asynchronous transmission, the method comprises the following steps: initial estimation and preprocessing: detecting initial active users and transmission time delay thereof through correlation peaks, and whitening received signals; the iterative joint detection and channel estimation module is used for iteratively updating channel information and data symbol information for multiple rounds based on a factor graph and a message passing algorithm; the data decoding module is used for decoding data based on a soft decision device; the detection and decoding performance is improved by transmitting external information among the modules; and the time delay parameter updating adopts a greedy search algorithm to obtain the optimal time delay. According to the method, the active user detection rate, the channel estimation precision and the data decoding accuracy under the condition that the receiving and transmitting ends are completely asynchronous are improved.

The invention discloses a fused salt heat storage and Carnot cell combined coal-fired unit peak-load regulation operation method, device and equipment, a medium and a product, and relates to the field of unit peak-load regulation operation. Acquiring information data; based on a power regulation demand prediction model, performing peak regulation demand prediction according to the information data to obtain a prediction result; the power regulation demand prediction model is obtained by adopting a multi-objective optimization model and performing time sequence analysis on a long-short-term memory network model; determining an energy scheduling strategy based on the prediction result; the energy scheduling strategy comprises a heat storage power coordination instruction and a heat release power coordination instruction; and according to the energy scheduling strategy, operation adjustment is conducted on the coal-fired unit, the fused salt heat storage subsystem and the Carnot battery subsystem based on the control system. The invention aims to improve the peak regulation performance of the coal-fired unit.

The invention provides a regional wind field multi-source heterogeneous work order data fast structuring system fused with a large language model, which comprises a plurality of modules, and is characterized in that a data input module receives various work order images; the OCR layout recognition module comprehensively recognizes the data, extracts key information, determines a spatial position and outputs text fragments with coordinates and layout anchor point information, and the rule field extraction module recognizes format category fields from the text fragments and calculates rule matching confidence; the semantic field recognition module recognizes descriptive fields from unstructured content and outputs related confidence information, the fusion decision module calculates final confidence of field candidates according to a predetermined function and judges output or complementation according to a threshold value, and the data consistency verification module is connected with an asset database to verify key information. The data complementation module generates complementation candidates and confidence coefficients, the man-machine collaborative closed-loop module pushes suggestions and receives feedback, and the result output module outputs standardized data. According to the method, the multi-source heterogeneous work order data can be effectively processed.

The invention provides a multi-station observation segmental arc association method and system for space debris. The method comprises the following steps: establishing an initial orbit of an unidentified segmental arc and an association information database; inputting an observation arc section; calculating an initial orbit of the observation arc section; traversing the initial track of the unidentified arc section and existing entries in the associated information database, sequentially judging whether the current observation arc section is associated with the initial track of the unidentified arc section and the existing entries in the associated information database or not until an associated object is found or all the existing entries are traversed, and if the associated object is found, judging whether the current observation arc section is associated with the existing entries in the associated information database. Modifying the initial track of the unidentified segmental arc and the content of corresponding items in the associated information database; if the associated object is not found, the information of the observed arc section is used as a new record to be inserted into the initial track of the unidentified arc section and the associated information database; the method is easy to implement, different association strategies are adopted for data of different time spans, association time consumption is reduced while association accuracy is guaranteed, and the method is suitable for association between single-station and multi-station observation arc section data.

The invention discloses an exhibition information synchronization and real-time updating management method and platform based on cloud computing. The method comprises the following steps: collecting multi-source heterogeneous exhibition information in real time through edge computing nodes; transmitting the collected heterogeneous data to a cloud computing center, carrying out format standardization, and carrying out semantic extraction on an unstructured text to generate a unified exhibition information data pool; periodic synchronization and instant synchronization based on event driving are carried out; when it is detected that multiple versions of the same information are updated, historical operation records of blockchain evidence storage are called, and a final effective version is generated in combination with preset priority rules and timestamp verification; and generating an adaptive information push packet according to the display capability and the interaction permission of the target terminal type. The method is used for solving the technical problems that in traditional exhibition information management, multi-source heterogeneous data integration is difficult, real-time updating response is insufficient, the unstructured text semantic processing capacity is weak, multi-source updating conflict resolution is not credible, and multi-terminal information pushing adaptability is poor.

The invention discloses an external visual system for forklift operation, and relates to the technical field of forklifts. Comprising an acquisition module, a processing module and an output module. The acquisition module stores a warehouse information data set, a cargo information data set, a forklift information data set, an equipment information data set and a problem information data set. According to the invention, through multi-factor decision fusion of a plurality of data sets stored in the acquisition module, a dynamic environment map of the processing module and an analysis model, collaborative optimization of cargo transportation safety and path planning robustness in a storage scene is realized; according to the system, historical accident data, dynamic obstacle contours and warehouse static structures can be fused in real time, high-risk areas are actively avoided, collision accidents and cargo damage risks are remarkably reduced, the problem of path failure caused by dynamic environment changes is effectively solved, and full-process intelligent safety guarantee is provided for high-density storage scenes.

The invention provides a multi-dimension-based information identification method and device and electronic equipment, and relates to the technical field of data processing, and the method comprises the steps: carrying out the data analysis processing of a plurality of pieces of information data transmitted by an identified risk transmitting end, determining a receiving end, and obtaining the information interaction data between the risk transmitting end and the receiving end; performing classification processing on the multiple pieces of information data according to information interaction data to obtain one-way information data and interaction information data; inputting the one-way information data, and / or the interaction information data and the interaction information into a trained information identification model for information identification processing to obtain an information probability value; and determining the information data with the information probability value greater than a preset probability threshold as abnormal information data. The condition that a single piece of information is normal but can be determined as abnormal information after multiple pieces of information are integrated can be effectively identified, so that the accuracy and comprehensiveness of information identification are improved.

The invention relates to the technical field of natural language processing, and discloses a diagnosis and treatment quality evaluation method and device, computer equipment and a storage medium. The method comprises the following steps: acquiring multi-source information data of a target patient in a treatment process; wherein the multi-source information data comprises target dialogue data and associated diagnosis and treatment data; performing reconstruction based on the multi-source information data to obtain an actual diagnosis and treatment thinking chain; wherein the actual diagnosis and treatment thinking chain is used for representing a diagnosis and treatment reasoning process when a doctor inquires a target patient; performing comparative analysis based on the actual diagnosis and treatment thinking chain to generate a diagnosis and treatment quality evaluation result for the target patient; wherein the diagnosis and treatment quality evaluation result is used for performing comprehensive quality control on the reasonability of the medical treatment process. By acquiring the multi-source information data containing the target dialogue data and the associated diagnosis and treatment data, the defect of single source of traditional quality control data is made up, and finally reasonable and comprehensive quality control can be performed on the whole diagnosis and treatment process.

The embodiment of the invention provides an address data matching method and related equipment, and belongs to the technical field of geographic information services. The method comprises the following steps: constructing an address annotation corpus according to input address information data and a preset address database; the method comprises the following steps: generating a geographic information embedding vector according to a preset geographic information knowledge graph, performing address element analysis in combination with an address annotation corpus to obtain an address element sequence so as to construct a dictionary tree, and performing similarity screening through a spatial hierarchical matching algorithm to obtain a similar address set; generating an address embedding vector matrix through a preset word embedding vector model, and performing feature extraction through a preset semantic feature extraction model to obtain semantic-level similar features; according to input address information data, multi-dimensional character similarity matching is carried out to obtain character-level similar features, then weighted fusion is carried out in combination with semantic-level similar features, and target matching address data is determined according to a weighted fusion result. According to the embodiment of the invention, the address data matching accuracy and efficiency can be improved.

The invention discloses a resource scheduling method and device based on IT asset health assessment, a medium and equipment, and the method comprises the steps: obtaining resource use data, network connection data and abnormal information data corresponding to each node in a distributed system, and carrying out the health degree scoring calculation based on the resource use data, the network connection data and the abnormal information data, obtaining a health degree score corresponding to each node; obtaining the priority of the service adapted to each node, and performing calculation based on the health degree score corresponding to each node and the priority of the adapted service to obtain a comprehensive evaluation value corresponding to each node; and scheduling resources based on the comprehensive evaluation value corresponding to each node. According to the method, the comprehensive evaluation value of multi-modal fusion is calculated, resource scheduling is carried out according to the comprehensive evaluation value, comprehensive and real-time comprehensive evaluation is carried out on the health condition of IT assets, corresponding scheduling processing is carried out according to the comprehensive evaluation condition, and the stability and reliability of the system are remarkably improved.

The invention discloses a data security risk analysis method and device, equipment and a storage medium, and the method comprises the steps: obtaining data access behavior information of a business system, the data access behavior information comprising business attributes; establishing a dynamic detection rule set based on the service attributes, wherein the dynamic detection rule set comprises risk judgment thresholds associated with the service attributes; constructing a service behavior baseline model associated with the service attributes according to the user historical behavior data; and performing association analysis on the data access behavior information, the dynamic detection rule set and the business behavior baseline model to obtain risk early warning information. According to the invention, the business behavior baseline model associated with the business attribute is constructed according to the historical behavior data of the user; the data access behavior information, the dynamic detection rule set and the business behavior baseline model are subjected to correlation analysis, the risk early warning information is obtained, compared with the prior art, the accuracy of data security risk detection is improved, and then the risk early warning false alarm rate is reduced.

The invention discloses a natural resource geographic information collection method and system, and belongs to the technical field of geographic information collection, and the method comprises the steps: obtaining natural resource geographic information data, and carrying out the data preprocessing of the multispectral image data in the data; optical abnormal data in the preprocessed multispectral image data are marked, meanwhile, ground abnormal data in ground survey fixed-point measurement data are marked, and geospatial alignment is carried out; identifying a highly overlapped region in the geographic space, and automatically attributing and judging an abnormal mode in the highly overlapped region as being caused by a specific unrecorded environment event; and adding an environmental event influence mark to the attributed natural resource geographic information data, wherein the environmental event influence mark is used for indicating the physical cause of the natural resource geographic information data exception. According to the method and the device, numerical value change relevance caused by the same physical cause in different natural resource geographic data types can be identified, and wrong geographic information interpretation results caused by data inconsistency in subsequent analysis are avoided.

The invention relates to the technical field of data processing, and discloses a land reserve space information data processing method and system based on big data, and the method comprises the steps: obtaining remote sensing image data, ground sensor data, social and economic data, land attribute data and planning data; unifying timestamps and space coordinates of multi-source data by adopting a space-time interpolation method, and extracting a land space topological relation by utilizing a GNN network; a CNN-Transform-LSTM model is adopted to carry out multi-modal feature fusion, and a multi-dimensional feature vector of land reserve is generated; inputting the multi-dimensional feature vector into a space-time diagram convolutional network to predict the short-term supply and demand change of the land reserve area, and generating an optimal reserve scheme through a genetic algorithm; constructing an interactive map based on a WebGL framework, and dynamically displaying a data processing result of the land reserve area; the data utilization rate and the data processing efficiency are improved.