315results about How to "Improve system performance" patented technology

The invention relates to the technical field of heat exchange modules, and discloses a multi-cavity cooperative control method and device for a micro-channel heat exchange module and electronic equipment, and the method comprises the steps: carrying out the numerical simulation calculation of a plurality of heat exchange cavities of the micro-channel heat exchange module, and obtaining a training data matrix; coefficient calculation and heat flow coupling relation analysis between cavities are carried out, and a heat flow distribution mathematical model is generated; substituting the heat flow distribution data, the temperature distribution data and the flow distribution data into a non-homogeneous heat conduction equation, and constructing a multi-objective optimization function; executing chaotic mapping processing and multi-target collaborative differential evolution to obtain an optimal control scheme set; carrying out Q-learning state value function solving, and generating a cooperative control instruction; and inputting the cooperative control instruction into an execution unit, and performing real-time adjustment and online updating on inlet temperature parameters and flow parameters of each heat exchange cavity to obtain a target heat flow distribution model. Therefore, information interaction and optimized cooperation among the heat exchange cavities are achieved, and the heat exchange efficiency is remarkably improved.

The invention relates to task scheduling, in particular to an intelligent task optimization method based on a self-adaptive multi-dimensional dependency graph and dynamic scheduling, which comprises the following steps of: inputting task information and resource information; constructing a self-adaptive multi-dimensional dependency graph according to the task information; in the task execution process, the task state of each task is monitored in real time, and the self-adaptive multi-dimensional dependency graph is dynamically updated; calculating the effective priority of the current task, and updating the effective priority of the current task according to the updated adaptive multi-dimensional dependency graph; dynamically scheduling the current task by adopting a dynamic scheduling algorithm; monitoring a task execution state and a resource use condition of each task in real time; according to the task execution state and the resource use condition, whether dynamic scheduling needs to be adjusted or not is judged until all tasks are executed; according to the technical scheme, the defect that in the prior art, accurate and efficient task optimization scheduling is difficult to carry out under the multi-dimensional dependency relationship between the tasks can be effectively overcome.

The invention provides a front-end performance optimization method based on cache management, and the method comprises the steps: S1, collecting and processing user behavior data, and obtaining target data; s2, analyzing a user behavior based on the target data, constructing a user behavior model, and predicting an access demand of a user by using a prediction algorithm to obtain a prediction model; s3, generating a caching strategy based on the user behavior model and the prediction model; and S4, storing resources on the client, the server and the content distribution network node based on the caching strategy. The cache hit rate is improved; the caching strategy is dynamically adjusted according to the actual use condition of the user, and the user requirement is more accurately met; the cache preloading mechanism can shorten the response time of the user request, can adapt to different user behaviors, and improves the user experience. The system and the electronic equipment provided by the invention have corresponding advantages.

The invention relates to the technical field of data transmission and updating, in particular to a data transmission and updating system and method of a cloud mobile phone. According to the technical scheme, the system comprises an intelligent network monitoring module, a dynamic bandwidth allocation module, a server load balancing module, an intelligent data synchronization module and a cache management module, and the intelligent network monitoring module monitors network conditions, including network bandwidth, network congestion degree and network stability, between a user terminal and a cloud server in real time. Through the synergistic effect of the intelligent network monitoring module, the dynamic bandwidth allocation module, the server load balancing module, the intelligent data synchronization module, the cache management module and the like, the network condition is accurately monitored, the bandwidth is reasonably allocated, the server load is optimized, the data synchronization and completeness are ensured, and the cache efficiency is improved; stable and reliable network connection, preferential key data transmission and rapid data synchronization and loading are brought to users, and the use experience of the cloud mobile phone and the overall performance of the system are greatly improved.

The invention relates to the technical field of real-time image superposition, in particular to a bridge inspection method and system based on AR, and the method comprises the following steps: shooting a bridge on site, capturing a real-time image of a structure, and recording vibration frequency, displacement change and stress data by using acceleration, displacement and strain sensors; and synchronously integrating the structure real-time image, the vibration frequency, the displacement change and the stress data, and naming the data as multi-dimensional dynamic monitoring data. According to the method, the vibration frequency, the displacement change and the stress data are integrated in real time, so that the real-time performance and the analysis depth of the multi-dimensional dynamic monitoring data are remarkably improved, the high fusion of a real-time image and a three-dimensional model is realized, the accuracy of data visualization is enhanced, an abnormal region is directly visible through the change of colors and textures, and the accuracy of data visualization is improved. According to the method, the structure safety monitoring intuitiveness and interactivity are improved, in addition, through time sequence analysis, structure changes under different environment conditions are accurately simulated, and prospective risk prediction is provided.

The invention relates to the technical field of sensor upgrading, in particular to a remote upgrading method and system for a tire pressure sensor. The method comprises the following steps: acquiring real-time state data of a tire pressure sensor; carrying out outlier parameter elimination on the real-time state data of the tire pressure sensor, and carrying out state diagnosis mining, so as to generate a state diagnosis report of the tire pressure sensor; performing upgrade demand prediction based on the tire pressure sensor state diagnosis report, and performing priority upgrade analysis to extract a plurality of upgradable sensors; performing byte-by-byte difference identification on the plurality of upgradable sensors based on preset latest version information, and performing incremental data encapsulation to generate a plurality of incremental upgrading data blocks; acquiring a historical running log of the vehicle; performing dynamic vehicle using behavior analysis and vehicle idle time period prediction on the vehicle historical operation log to generate a plurality of idle prediction time periods; the upgrading efficiency and the safety performance of the tire pressure sensor are improved.

The invention relates to the technical field of safety evaluation, in particular to an ultra-deep soft soil foundation pit safety evaluation method and system, and the method comprises the following steps: obtaining the geological data of an ultra-deep soft soil foundation pit, recording the soil type, soil density, underground water level and temperature data, carrying out the data arrangement and formatting, and generating a geological data record sheet. According to the method, the detailed geological data of the ultra-deep soft soil foundation pit are acquired and arranged, the accuracy and the applicability of the basic data are enhanced, so that subsequent analysis is carried out according to clear actual conditions, and the timeliness and the accuracy of risk prediction are ensured by directly associating prediction of mechanical behaviors with risk assessment; the risk assessment model can be dynamically adjusted, the effectiveness and accuracy of early warning are improved, the risk dependency relationship model and the monitoring scheme are integrated, theoretical and actual operations are effectively linked, the systematicness and adaptability of construction safety management are effectively improved, and the accident prevention capability is remarkably improved.

The invention provides a robot system based on self-adaptive cruise and remote operation and a control method thereof, and belongs to the field of robot inspection, the system comprises a six-axis mechanical arm, an intelligent inspection robot, an automatic inspection task module and a remote teleoperation control unit; the intelligent inspection robot carries a six-axis mechanical arm and an automatic inspection task module, the automatic inspection task module comprises a preset inspection task, the remote teleoperation control unit sends a control instruction of an operator to the intelligent inspection robot through wireless communication, and the control instruction comprises inspection path planning and operation tasks. The intelligent inspection robot performs an inspection task according to a preset inspection task of the automatic inspection task module or a control instruction sent by the remote operation control unit, and the six-axis mechanical arm is used for executing a target operation task. Through integration of advanced sensor technology, image processing technology, artificial intelligence algorithm and wireless communication technology, efficient, accurate and safe inspection of a complex environment is realized.

The invention discloses a modern mobile informatization equipment management platform construction method and system, and relates to the technical field of informatization equipment management.The method comprises the steps that a management platform based on the full life cycle of equipment is used, and equipment life cycle nodes are associated; optimizing an equipment inspection flow, formulating an inspection standard and a dynamic task, and uploading data in real time in combination with a mobile terminal; based on multi-source data fusion analysis, equipment operation parameters are optimized, and decision support and abnormity early warning are provided. According to the method disclosed by the invention, the systematicness and comprehensiveness of equipment management are improved by establishing the full-life-cycle management platform and associating the equipment nodes; an embedded monitoring module is combined with a prediction algorithm, so that the equipment failure rate and the non-planned downtime are reduced, and the high efficiency and the reliability of equipment management are ensured; the abnormal early warning and decision support functions provide comprehensive optimization strategies and emergency response means for managers, so that the management efficiency and the equipment operation safety are improved.

The invention discloses an urban drainage network optimization design system, and relates to the technical field of urban drainage optimization, a data collection and preprocessing module is utilized to collect basic data, a parameter determination module is utilized to determine the rainfall intensity, the ground permeability, the sewage concentration and the pipeline cleanliness, and a comprehensive evaluation optimization module is utilized to optimize the urban drainage network. The drainage efficiency and cost effectiveness of rainwater and sewage are calculated and output respectively, a comprehensive evaluation result reflecting the sustainability of the whole drainage system is calculated and output in combination with the drainage efficiency and cost effectiveness of rainwater and sewage, and a detailed drainage network optimization design scheme is analyzed and formulated in combination with the drawn line graph. According to the method, innovative means of refined parameters, comprehensive cost-benefit analysis, systematic comprehensive evaluation and an intelligent feedback mechanism are introduced, and a more scientific, comprehensive and efficient solution is provided for planning, design, operation and maintenance of the urban drainage network.

The embodiment of the invention provides a software test recommendation method and device, equipment and a storage medium. The method comprises the following steps: performing feature extraction on a technical document of to-be-tested software to obtain test features of the to-be-tested software; according to a similarity score between the test feature and a historical test feature corresponding to a historical test demand, screening out a target historical test demand meeting a condition from the historical test demand; performing feature screening on the test features corresponding to the target historical test requirements based on an association rule analysis algorithm to obtain target test features; performing clustering processing on the target test features based on a preset clustering dimension to obtain software test suggestion information under the preset clustering dimension; and recommending the software test suggestion information to a user. According to the embodiment of the invention, quality fluctuation caused by experience and ability level differences of testers can be avoided, the systematicness and consistency of test suggestions are improved, and the coverage of the test suggestions is improved.

The invention discloses a data transmission and control method and system based on a Beidou short message, and relates to the technical field of remote monitoring and communication, and the method comprises the steps: a Beidou slave station receives remote signaling and telemetering data, carries out the data processing of the received data, packages the data into a Beidou short message format, carries out the data transmission through a multi-mode command transmission protocol, and carries out the data transmission through a Beidou short message transmission protocol; the method comprises the following steps: receiving command data converted by a Beidou master station, monitoring a system in real time through a command execution state, feeding back an execution progress and state to the master station in real time, automatically executing a recovery process through a fault self-healing mechanism when data transmission is abnormal, and automatically adjusting data transmission frequency and power by utilizing a self-adaptive energy management algorithm, so as to realize real-time data transmission. And through the data transmission prediction model, predicting a data transmission demand, and adjusting a data refreshing strategy in advance. Through the adaptive energy management algorithm and the prediction model, the data transmission frequency and power are dynamically adjusted, the energy consumption is optimized, and the data transmission efficiency and real-time performance are improved.

The invention discloses a compressed air energy storage underground cavern site selection method based on multi-scale stability evaluation. The method comprises six main steps of establishing a multi-scale evaluation system, evaluating the stability of a regional structure, identifying and analyzing a safety island, analyzing the stability of a site in detail, comprehensively integrating multi-scale evaluation results and verifying the evaluation results. According to the method, a multi-scale structure stability evaluation system is established, a safety island concept and an identification method thereof are provided, an innovative scale conversion and data fusion algorithm is developed, comprehensive and multi-level evaluation from macroscopic to microscopic is realized, and the accuracy and reliability of CAES underground cavern site selection are remarkably improved.

The invention relates to the technical field of computers, and discloses a host firewall software strategy collection and analysis method. The method comprises the steps of S1, deploying acquisition agents in a distributed manner, and acquiring policy data of a host firewall; s2, carrying out standardized analysis and storage on the collected data; s3, uploading the standardized strategy data to a central management node through an incremental synchronization mechanism; s4, constructing a rule dependency graph based on the rule data at the central management node; and S5, performing conflict detection and redundancy analysis on the host firewall rule by using the rule dependency graph. Priority conflict, coverage conflict and mutual exclusion conflict detection is performed on the rule set through the rule dependency graph, the priority conflict detection ensures the execution logic consistency of the rule, the coverage conflict detection reduces the redundant execution of the rule, and the mutual exclusion conflict detection avoids the rule combination of logic contradictions. And through systematic conflict detection, the execution accuracy and reliability of the rule set are remarkably improved.

The invention discloses a method and a system for improving data interaction efficiency of a hyper-converged architecture, relates to the technical field of hyper-converged architectures, and aims to solve the problems of network bottleneck and storage delay of data transmission among different virtual machines or containers in the conventional hyper-converged architecture. According to the scheme, a data transmission optimization module needs to be introduced into a hyper-converged architecture, so that the data access speed and the network efficiency are improved through data prefetching and an intelligent routing technology; the distributed cache module is used for relieving the pressure of a single node and ensuring accurate synchronization of data through data locality optimization and cache consistency management; the parallel data processing module is used for improving the data processing efficiency through task parallelization and data fragmentation technologies; and the self-adaptive load balancing module is used for dynamically adjusting resource allocation according to the system load and the resource use condition so as to realize the balance of calculation, storage and network load. The method reduces the delay, improves the throughput, and improves the overall performance and resource utilization rate of the system.

The invention relates to a sparse antenna array synthesis method based on neural network intelligent solution, and the method comprises the steps: carrying out the full-wave simulation of an antenna unit according to an array synthesis requirement, obtaining a unit active directional diagram, and constructing a unit active directional diagram database; constructing an initial sample set according to the unit active directional diagram and the array numerical simulation model; randomly dividing the initial sample set into a training set and a verification set, carrying out offline training by utilizing the training set, and carrying out array comprehensive solution on verification set data; judging whether the resolving result meets the arraying requirement or not, if not, adopting a convex optimization algorithm to assist calculation, updating the data set, and retraining; otherwise, outputting the neural network model; and through the model, according to the unit spacing constraint and the active directional diagram, sparse antenna array synthesis is carried out, and array topology is output. The method can achieve the comprehensive settlement of the antenna array, is high in speed, is high in efficiency, and better accords with a real array working environment.

The invention provides a nonlinear dynamic disaster deep well ground pressure monitoring and early warning method and system, and relates to the technical field of geological engineering and disaster early warning, and the method comprises the steps: selecting a state variable and a control variable according to an abrupt change theory, a grey theory, a Verhulst model theory, a Verhulst inverse function mode theory and a nonlinear dynamic theory; analyzing the variables and the key parameters to obtain an analysis result; according to the analysis result, predicting the instability time of the rock mass to obtain a prediction result; according to a prediction result, simulating a process from deformation to instability of the rock mass to obtain predicted rock mass instability time; the acoustic emission time sequence, the stress time sequence and the displacement time sequence serve as observation sequences, the dynamic relation between the observation sequences is described, and an inversion theory is used to determine inversion parameters; according to the prediction result, rock mass instability time and inversion parameters are predicted, the stability of the rock mass is evaluated, and an early warning result is obtained. According to the invention, comprehensive evaluation and early warning of the stability state of the rock mass can be realized.

The invention discloses an aromatherapy intelligent margin calculation method based on vehicle body data dynamic perception. The method comprises the following steps: S1, generating an initial data set; s2, inputting the initial data set into a multi-channel variational encoder, and outputting hierarchical feature representation; s3, inputting the hierarchical feature representation into a spatio-temporal context sensing module to generate spatio-temporal feature representation; s4, inputting the spatial-temporal feature representation into a heterogeneous feature mapping layer to generate a unified data representation; s5, inputting the unified data representation into a dynamic prediction regulation and control module, and generating an optimized feature representation; s6, inputting the optimized feature representation into an aromatherapy residual amount prediction model, and performing residual amount prediction by using a Gaussian mixture process; s7, inputting an aromatherapy residue prediction result into a feedback integrator, and carrying out self-supervised learning; and S8, integrating to a vehicle-mounted system, displaying an aromatherapy allowance state and sending a personalized notice. According to the method, accurate prediction and calculation of the vehicle-mounted aromatherapy allowance are realized by utilizing multi-channel variational coding, spatio-temporal context perception, a Gaussian process and the like.

The invention discloses a photovoltaic module fault cause determination method and device, a storage medium and an electronic device, and the method comprises the steps: obtaining the operation data of a photovoltaic module in the operation process, and the operation data at least comprise one of the first operation data of a photovoltaic array and the second operation data of a boost converter, third operating data of the inverter; inputting the operation data into a fault detection model to obtain a fault reason output by the fault detection model, the fault detection model being obtained by training with historical operation data as an input sample and historical fault reasons as output samples, the model parameters of the fault detection model are obtained through optimization based on a golden eagle optimization algorithm. By adopting the technical scheme, the technical problem that the fault reason of the photovoltaic module cannot be comprehensively and accurately judged is solved, and the accuracy and comprehensiveness of the fault reason of the photovoltaic module are improved.

The invention provides a communication method of multi-application communication based on a serial interface and a storage medium, the communication method is applied to a protocol stack of multi-application communication, a hardware layer of the protocol stack uses an asynchronous full-duplex serial interface, and the communication method comprises the following steps: establishing a point-to-point transmission channel between applications through the asynchronous full-duplex serial interface; a sending end sets sending numbers for data packets, the data packets are packaged into data frames through a data link layer of a protocol stack, and the data frames are sequentially sent through a transmission layer of the protocol stack according to priorities of point-to-point transmission channels of different applications in all the applications; and the receiving end receives the data frame and verifies the transmission integrity of the data packet according to the sending number. The technical problems that the design of an existing communication method in a multi-chip ECU board is complex, and communication of multiple applications in two chips through one interface cannot be achieved are solved.

The invention discloses a question and answer strategy construction method based on a Java language and a large model. The method specifically comprises the following steps: preprocessing question data based on the Java language; the corresponding domain model receives the preprocessed problem data, vector matching is carried out based on a QA knowledge base, and a matching score is set; selecting a corresponding cue word template from a preset cue word template library based on features extracted from the question data, and then calling a large model to generate answer data; inputting the answer data into a client library, and forming customer evaluation data after customer evaluation; counting and analyzing the reply accuracy and generating a report based on customer evaluation data; and setting a threshold value of the accuracy rate of the reply. According to the method, the Java language and the large model are combined, data reading, cleaning, feature extraction and domain model matching are efficiently and accurately processed, the precision and stability of follow-up question and answer strategy construction are improved, diversified user requirements are met, and complex problem scenes are dealt with.

The invention discloses a space-air-ground integration-oriented full-decoupling network non-feedback transmission and resource dynamic allocation method. A solution is provided for space-air-ground multi-node cooperation resource management. The method comprises the steps that a channel state information prediction model based on deep learning replaces traditional feedback signals with user geographical location information, and multiple-input-multiple-output transmission is achieved; and a many-to-one matching model is designed and is used for realizing adaptive allocation of spectrum resource blocks among space-air-ground heterogeneous nodes, so that the matching stability is ensured, and the method has the characteristics of low complexity and rapid convergence. For cooperative transmission of multiple nodes and resource allocation among heterogeneous nodes, the spectrum efficiency of the system is improved through non-feedback channel state information prediction and a resource allocation mechanism. Compared with a single connection mode and polling-based resource scheduling in a traditional network, the flexible resource allocation algorithm disclosed by the invention remarkably improves the network capacity and improves the user communication quality.

The invention discloses an intelligent operation and maintenance service method and system for an electronic port, and relates to the technical field of operation and maintenance services of the electronic port, and the system comprises a data collection module which is used for monitoring the operation state of equipment in the electronic port in real time, and obtaining the operation parameters of the equipment; and the data analysis module is connected with the data acquisition module, and performs preprocessing based on the acquired operation parameters to obtain lossless parameters. According to the intelligent operation and maintenance service method and system for the electronic port, reasonable resource allocation, workload balance of operation and maintenance personnel and shortening of processing time are realized, the operation and maintenance efficiency is improved, it is ensured that the system can be rapidly processed when a fault occurs, the influence of the fault on electronic port business is reduced, and the service quality of the electronic port is improved. Reasonable resource allocation, workload balance and processing time shortening can be realized, and the operation and maintenance efficiency and the system performance are improved.

The invention provides a zero-copy rapid transceiving device, a data sending method and a data receiving method, and relates to the technical field of network communication, the zero-copy rapid transceiving device comprises a network card in which a direct memory access controller and an associated annular cache region are configured; the kernel protocol stack is configured with a data cache structure body, and a data pointer of the data cache structure body and a packet descriptor of the annular cache region are configured to point to the same memory region; when the network card receives external data, the direct memory access controller copies the data to the memory area according to the direction of the packet descriptor so that the data can be processed by the kernel protocol stack, and when the kernel protocol stack sends the data, the data is copied to the memory area according to the direction of the data pointer so that the data can be sent by the direct memory access controller. The method has the beneficial effects that data copying is not needed in a driving layer message data processing process, so that storage resources are effectively saved, the load of a CPU (Central Processing Unit) is reduced, and the network bandwidth and the system performance are effectively improved.

The invention relates to the technical field of employee management, and discloses an employee operation evaluation method and device, electronic equipment and a storage medium, and the method comprises the steps: obtaining a target shift corresponding to a target employee, carrying out the matching of production data based on the target shift, obtaining initial data, responding to a target index selected from pre-established evaluation indexes, and carrying out the operation evaluation of the target employee. According to the collection duration corresponding to the target index and a target scoring item corresponding to the target index, target data is determined from the initial data, scoring is carried out based on the target data and a preset scoring rule, a scoring result is obtained, the scoring rule comprises a mapping relation between the target data and a scoring score corresponding to the target scoring item, and the scoring result is obtained. Evaluating the operation of the target employee according to the scoring result; through the method, a more practical and more accurate employee operation evaluation method is provided.

The present invention relates to the field of automatic design optimization technology, and in particular to an automatic arts and crafts design optimization method based on intelligent data. The method comprises the following steps: obtaining user demand input data; performing part-of-speech analysis on the user demand input data to generate user demand input part-of-speech data; performing sentence segmentation on the user demand input data using the user demand input part-of-speech data to generate user demand input sentences; performing design creative description analysis on the user demand input sentences to obtain a creative description keyword cloud map; obtaining an arts and crafts database; performing an initial arts and crafts map design on the user demand input sentences based on the arts and crafts database to obtain an initial arts and crafts demand map; performing simulated iteration replacement on the initial arts and crafts demand map according to the creative description keyword cloud map to obtain a first arts and crafts demand update map. The present invention improves the intelligence, accuracy and efficiency of arts and crafts design optimization through intelligent data processing and analysis.

The invention relates to the technical field of archive management, in particular to an archive digitization full-process standard management system, which comprises a project identification module used for obtaining effective project information; the project generation module is used for generating archive project information and archive project nodes; the team generation module is used for generating an archive project team and a target archive project; the association identification module is used for identifying associated archive items; the migration judgment module is used for judging the migration necessity of the associated file project; the migration execution module is used for executing the migration scheme; the migration optimization module is used for optimizing the execution process of the migration scheme; and the management repair module is used for repairing the target archive project in the archive management process. According to the invention, digital full-process standard management is carried out on the archives, intelligent association of automatic optimization identification, dynamic restoration and archive management processes is realized, and the archive management efficiency is improved.

The present invention belongs to the field of construction site safety technology, specifically a construction site construction safety assessment system, the system includes: a scene reconstruction design module, a data perception module, a data communication module and a data processing module. The present invention has the beneficial effects of being able to realize real-time, accurate and comprehensive data collection and transmission of construction sites, improving the data quality and timeliness of construction safety assessments; being able to realize clear, intuitive and dynamic scene reconstruction and display of construction sites, improving the visualization and interactivity of construction safety assessments; being able to realize scientific, objective and consistent risk analysis and assessment of construction sites, improving the systematicness and reliability of construction safety assessments; being able to realize efficient, accurate and intelligent design and construction optimization and adjustment of construction sites, improving the optimization and automation of construction safety assessments.

The invention relates to a calculation method for concentration ratios of rainfall in different forms, and the method comprises the steps: obtaining meteorological data and elevation data of a to-be-measured time period of a research region, and generating a wet bulb temperature and a threshold temperature according to the meteorological data and the elevation data; wherein the threshold temperature comprises a critical high temperature and a critical low temperature; performing temperature judgment on the wet bulb temperature based on the threshold temperature, acquiring different rainfall types of the research area, and acquiring rainfall amounts of different types of rainfall in combination with rainfall data; calculating the cumulative rainfall days and the cumulative rainfall amount of different types of rainfall through the rainfall amount, calculating the concentration ratio of different rainfall types by using the regression coefficient, and further calculating the concentration ratio and the rainfall concentration period of the rainfall in the region by combining the vector azimuth angle. The method can solve the problem that the spatial and temporal distribution of the concentration ratio of different rainfall types cannot be effectively quantified, and makes up for the defect that the existing index cannot accurately reflect the change of different rainfall types and the influence of the concentration degree on regional water resource management and weather prediction.

The invention discloses a data mining evaluation system for urban and rural planning construction land, and relates to the technical field of wind power data processing, and the system comprises a multi-dimensional data acquisition module which is used for acquiring multi-dimensional data of target planning land. And the evaluation relation establishing module is used for respectively establishing evaluation relations between the multi-dimensional data and the rationality of the planned land. And the feature node mining module is used for taking the data of each dimension as feature nodes, mining evaluation relevance of the feature nodes and establishing node connection edges. And an evaluation interaction network construction module which uses the evaluation relation to fit and connect the feature nodes and the connection edges and constructs the evaluation interaction network. And the aggregation evaluation module is used for performing feature segmentation according to the evaluation interaction network to obtain an evaluation feature multi-layer structure, performing hierarchical feature aggregation based on the evaluation feature multi-layer structure, generating an aggregation evaluation value and planning rationality evaluation. Therefore, the technical effects of improving the data mining depth and systematicness and improving the evaluation accuracy are achieved.