8149results about How to "Improve compatibility" patented technology

The invention relates to the technical field of data processing, and discloses an industrial one-stop multi-source data acquisition and monitoring system and equipment, and the system comprises a data acquisition module which is used for obtaining multi-source industrial monitoring data and generating a data stream input node; the data preprocessing module is used for processing the input data in the data flow model to generate a standardized data flow; the data conversion module is used for dynamically converting data nodes in the standardized data stream according to different data protocols to generate a compatible data stream; the task scheduling module is used for optimizing the data flow and distributing the data flow to a target node according to the compatible data flow in combination with a node priority and a dynamic scheduling strategy in the data flow model; and the exception detection module is used for carrying out exception state analysis on the optimized data stream and judging whether an exception exists or not according to a preset rule. According to the technical scheme, the compatibility and reliability of the monitoring system can be improved.

The invention discloses a data transmission method, a protocol converter and a monitoring system of energy storage equipment, and relates to the technical field of data transmission. The protocol converter can obtain the protocol characteristics of the communication protocol adopted by the energy storage equipment, and identifies the target protocol type of the communication protocol based on the protocol characteristics. And then, the protocol converter can perform data format conversion on the data to be transmitted based on the target protocol type, and then transmit the data after format conversion. That is, the protocol converter can adapt to communication protocols of different energy storage devices so as to interact with the energy storage devices of different communication protocols. Therefore, on one hand, efficient and unified monitoring of the energy storage devices with different communication protocols can be realized through the protocol converter, and the compatibility and monitoring efficiency of the energy storage devices with different communication protocols are improved; and on the other hand, the monitoring system comprising the protocol converter can adapt to energy storage equipment with continuously changing communication protocols, and the flexibility and expandability of the monitoring system are enhanced.

The invention discloses a multi-source three-dimensional model lightweight processing and lossless compression supporting method, system and device and a storage medium, and relates to the three-dimensional technical field, and the method comprises the following steps: carrying out format compatibility check on an imported three-dimensional model, and analyzing the geometric structure, texture characteristics and material attributes of the model; the geometric structure of the three-dimensional model is simplified by adopting a quadratic error measurement algorithm and edge folding, the simplified model is optimized through edge segmentation operation, and a lightweight model is obtained; and compressing geometric data of the lightweight model by using a data compression algorithm, and compressing texture data through predictive coding to complete lossless compression of the three-dimensional model. According to the method, the loading speed and the real-time rendering efficiency are remarkably improved by reducing the size of the three-dimensional model file and optimizing the texture compression algorithm. The lossless compression technique ensures that a high-quality visual effect is kept in the lightweight process, the lightweight model reduces the storage space requirement, and the energy consumption of data transmission and processing is reduced.

The invention relates to a photovoltaic grid-connected inverter and an alternating current side starting method of the photovoltaic grid-connected inverter, and the inverter comprises a bus capacitor, a DC / AC inverter circuit, a control unit and a pre-charging circuit. The input end of the DC / AC inverter circuit is connected with the bus capacitor, and the output end of the DC / AC inverter circuit is connected with a power grid; the input end of the pre-charging circuit is connected with a power grid, the output end of the pre-charging circuit is connected with the bus capacitor, and the pre-charging circuit is used for taking electricity from the midpoint of the grid-connected relay to charge the bus capacitor; the bus capacitor is used for starting the DC / AC inverter circuit after charging is completed; the control unit is used for controlling work of the pre-charging circuit. According to the invention, the AC side starting of the inverter can be realized, the starting process is safer, and the work is stable and reliable.

The invention discloses an operation regulation and control method and system for a distributed new energy photovoltaic power station, and relates to the technical field of new energy, and the method comprises the steps: recognizing a power station, building a monitoring system, collecting and monitoring key equipment data through the system, so as to obtain historical and real-time operation data, and predicting photovoltaic output and load based on the data to obtain predicted values, calculating power deviation, inputting the deviation into an optimal scheduling model to obtain a strategy, and adaptively regulating and controlling the operation state of the power station according to the strategy. The technical problems of unbalanced power generation and power utilization, low operation efficiency, poor stability, high cost and poor power grid compatibility caused by the fact that efficient and self-adaptive optimal scheduling cannot be performed according to accurate photovoltaic output and load prediction in the prior art are solved, accurate balance of power generation and power utilization is achieved, and the power generation efficiency and the power utilization efficiency are improved. The operation efficiency and stability of the power station are remarkably improved, the operation cost is reduced, and the compatibility with a power grid is enhanced.

The invention discloses a remote regulation and control LED lighting system based on the Internet of Things, and relates to the technical field of LED lighting systems, comprising an LED lighting equipment module which comprises an efficient lamp, a microcontroller, an Internet of Things communication module, a remote control terminal module supporting multi-protocol and encryption, having Mesh networking, a multi-terminal control, having multiple functions and innovation formulas, and a sensor module; the intelligent LED lighting control system has the advantages that environment information is collected, the data management and analysis module stores and analyzes data, energy-saving management and the like are achieved, all the modules work cooperatively, and the functions of remote intelligent regulation and control, fault self-inspection, butt joint with other systems and the like of LED lighting are achieved. Through collaborative innovation of multiple modules, remote intelligent regulation and control of LED lighting are realized, the lighting quality and user experience are improved, energy is saved, consumption is reduced, the system has the functions of fault self-checking and alarming and the like, the reliability and compatibility of the system are improved, and the diversified requirements of modern lighting systems are met.

The invention provides an erasure code compatible read-write method and system based on a bidirectional data access agency, and relates to the technical field of distributed storage, and the method comprises the steps: employing multi-agent reinforcement learning to construct a heterogeneous resource portrait and optimize task allocation, combining a space-time graph convolutional network and a federated learning framework to construct a data format conversion model, and constructing an erasure code compatible read-write model; data features are analyzed through an encoder based on an attention mechanism, a fragmentation strategy is generated, self-adaptive encoding is achieved through a capsule neural network, data integrity verification and repairing are conducted through a double-layer space attention network and a graph attention network, the data access efficiency of a heterogeneous storage system is improved, data format compatibility is enhanced, and the data access efficiency is improved. And the data integrity is ensured.

The invention provides a data fusion sharing method for multi-source heterogeneous power big data, which comprises the following steps: when receiving multi-source heterogeneous power data, carrying out dynamic protocol adaptation, and converting multi-source heterogeneous power data formats of different protocols into a current system internal standard format; performing data quality evaluation on the data converted into the standard format in the current system, and when a quality evaluation result does not meet a quality requirement, performing data restoration; analyzing the data passing the data quality evaluation or restoration, determining the correlation among different data sources, and fusing the data according to the correlation among the different data sources; and performing distributed storage on the fused data for distributed indexing and access. By implementing the method and the system, efficient fusion and sharing of multi-source heterogeneous data can be realized, the intelligent level of data management and analysis of a power system is improved, and the requirements of an intelligent power grid on data instantaneity, accuracy and safety are met.

The invention provides an innovative deep concealed ore deposit detection method, which comprehensively utilizes geology, geophysics, geochemistry and remote sensing technologies, and realizes effective integration of multi-source geological data by developing an advanced data fusion algorithm. According to the method, data collected by geological survey, wide-area electromagnetic method exploration, hydrocarbon-mercury superposition halo analysis and aviation hyperspectral remote sensing are subjected to standardized preprocessing, so that the consistency and accuracy of the data are ensured; and then, deep analysis is carried out on the fused data by utilizing machine learning and statistical analysis technologies so as to identify and predict mineralization modes and abnormal regions. Finally, a three-dimensional geologic model is constructed, the form and distribution of an ore deposit are visually displayed, and a scientific basis is provided for geological exploration. The method is characterized in that a multi-source data fusion technology and mineralization mode identification automation and precision are realized, so that the efficiency and the accuracy of deep hidden ore deposit detection are remarkably improved.

The invention discloses an intelligent centralized control and protection integrated system for a high-low voltage switch cabinet, relates to the technical field of electric power automation, and solves the problems that an existing centralized control system is lagged in data processing, incompatible in communication protocol and difficult in fault positioning. Running parameters and equipment state parameters of each high-low voltage switch cabinet are monitored in real time through a distributed data acquisition module; different communication protocols are automatically identified and adapted through the communication transmission module; real-time data analysis, fault early warning and state evaluation are carried out through a deep analysis module, and an early warning mechanism is triggered when a potential fault is early warned; the fault diagnosis module is used for quickly positioning a fault source and generating a maintenance suggestion, and the remote interaction module is used for providing a graphical user interface, displaying the real-time state of the system and allowing a user to remotely monitor and operate; according to the invention, the performance, compatibility and usability of the system are obviously improved.

The invention relates to a database query method and device based on a large language model agent and electronic equipment, and the method comprises the steps: obtaining and analyzing query request information, recognizing a query request intention type, carrying out the problem splitting of the query request information according to the query request intention type, and obtaining sub-query request information; searching and obtaining an SQL statement corresponding to the sub-query request information in the target knowledge base according to the category of the query request intention, constructing and generating an SQL statement prompt word and sending the SQL statement prompt word to the large language model when the SQL statement is not searched, executing according to the returned SQL statement to obtain a sub-query result, integrating the sub-query result and obtaining a query result of the query request information, and generating a data visualization code based on the large language model, executing and outputting a query result and a visualization display result thereof. By combining natural language processing, a large language model and a multi-item optimization technology, the efficiency and usability of data query are greatly improved, and non-technical users can conveniently analyze complex data.

The invention relates to the technical field of quality traceability management, in particular to an organic fertilizer quality safety traceability management method based on multi-source data. The method comprises the following steps: collecting organic fertilizer source data in real time from links of organic fertilizer production, circulation, storage and use, performing standardization processing, and performing production batch synchronous set processing and traceability association connection file establishment to generate an organic fertilizer multi-source data traceability association connection file; and carrying out production batch tracing extraction processing on the organic fertilizer multi-source data traceability association connection file, carrying out organic fertilizer quality index evaluation analysis and quality index error limitation analysis, carrying out organic fertilizer quality safety abnormity traceability processing and abnormity decision support processing, and generating an organic fertilizer quality safety abnormity problem decision support report. Therefore, the corresponding organic fertilizer quality safety abnormity traceability problem management work is executed. The scientificity and accuracy of organic fertilizer quality safety management can be improved.

The invention discloses an Internet of Things equipment access protocol component development method, which is used for quickly developing an Internet of Things equipment access protocol analysis and processing component at an Internet of Things platform side, and comprises the following steps: S1, constructing a protocol analysis and processing general framework according to the protocol analysis and processing component of an Internet of Things platform; s2, abstracting a specific logic processing part of a protocol in the general framework into a method / function interface; s3, constructing a protocol expert AI knowledge base for data learning; s4, constructing an AI large model and a multi-agent processing flow, selecting a specified large model, configuring related parameters, extracting required parameter extraction / coding logic, and generating an interface implementation code; s5, integrating each generated interface implementation code with the universal framework; and S6, testing, adjusting and optimizing the integrated access protocol analysis and processing component. According to the method, the unified development template can be provided, so that the development technical threshold is reduced, and the development efficiency is greatly improved.

The invention discloses a back contact battery, a manufacturing method thereof and a photovoltaic module, relates to the technical field of photovoltaic, and aims to enable the back contact battery to have a relatively low hot spot risk and improve the working reliability of the back contact battery. And meanwhile, the back contact battery has relatively high working efficiency in a forward voltage region. A back contact cell includes a semiconductor substrate, a first doped semiconductor portion, a second doped semiconductor portion, and a transparent conductive layer. In the reverse electric leakage area, the part, extending into the overlapping area from the second area, of the transparent conductive layer is a first transparent conductive part, and the first transparent conductive part is electrically connected with the first doped semiconductor part through the second doped semiconductor part. The width of the first transparent conductive part in the first direction is W1, the width of the overlapping area in the first direction is W2, and the ratio of W1 to W2 is larger than or equal to 10% and smaller than or equal to 90%.

The invention belongs to the field of fault diagnosis, and particularly relates to a main shaft bending common characteristic diagnosis system based on a stacking integration method, and the system comprises the following modules: a sensor module which is used for collecting a vibration signal of a main shaft in real time; the data acquisition and processing module is used for converting an analog signal into a digital signal and preprocessing the signal acquired by the sensor; the feature extraction module is used for extracting features from the preprocessed vibration signals; the machine learning diagnosis module analyzes and classifies the extracted features by using stack integration based on a plurality of trained machine learning models, and judges the health state of the main shaft; and the output module is used for outputting the diagnosis result and sending out an alarm signal when abnormality is detected. Real-time monitoring and automatic diagnosis of the main shaft bending fault are achieved, compared with a traditional method depending on expert experience and manual detection, the fault detection efficiency and accuracy can be greatly improved, and misjudgment and missed judgment risks caused by human factors are reduced.

The invention discloses a light spot real-time monitoring and feedback focusing system and method for laser processing. The system comprises a laser processing module, an emission light source module, a power monitoring module, a light spot monitoring module and an automatic control module. The emitting light source module is used for emitting laser beams; the power monitoring module is used for monitoring the laser power emitted by the emitting light source module; the light spot monitoring module is used for monitoring light spots of diffuse reflection light after the laser is emitted to the surface of the workpiece; the automatic control module sets reference signals of the following parameters: processing laser power and shape, position and size of a processing light spot; and according to the reference signal and the corresponding feedback signal, the laser emission parameter and the laser incident workpiece surface parameter are automatically adjusted, so that the error between the reference signal and the corresponding feedback signal is within a set precision range. According to the method, the light spot form and the light intensity in the machining process are dynamically monitored, and the light spot form and the energy in the laser machining process are adjusted in real time through feedback.

The invention provides a WEB browsing real-time rendering method and system based on distributed rendering, and relates to the technical field of distributed rendering, and the method comprises the following steps: receiving a rendering request from a user terminal browser, obtaining page data of a target webpage according to the rendering request, preprocessing the page data, analyzing the preprocessed page data, and displaying the analyzed page data. Obtaining a DOM tree structure and a CSSOM tree structure of the page, and constructing a rendering tree adaptive to the user terminal according to the DOM tree structure, the CSSOM tree structure and the equipment parameters; dividing the rendering tree into a plurality of sub-rendering trees, transmitting sub-rendering results generated by the plurality of distributed rendering nodes to a synthesis service node, performing image compression, transmitting the compressed rendering result data to a user terminal browser, receiving and decompressing the rendering result data in the user terminal browser to obtain a rendering result bitmap, and displaying the rendering result bitmap in the synthesis service node. And displaying the information to the user for real-time interactive browsing of the user.

The invention discloses an audio stream adaptive decryption method, system and device and a storage medium. The method comprises the following steps: acquiring an MPEG-DASH list file and analyzing the MPEG-DASH list file; the standard DRM interface is initialized; performing feature extraction on the identified audio segmentation information in the audio segmentation mode, and dynamically adjusting a segmentation request and processing logic according to the extracted features to perform adaptive segmentation downloading and preprocessing; extracting the encryption parameter to identify an encryption mark of the target audio stream platform, and selecting a corresponding decryption algorithm according to the encryption mark to decrypt the current audio segment; and performing audio frame reconstruction on the decrypted data to form an updated audio stream, caching the updated audio stream to a preset cache region based on a self-adaptive buffer strategy, and outputting the final audio stream to ensure the continuity of the final audio stream and realize efficient parallel processing of decryption and playing, so that the decryption efficiency is improved, and the user experience is improved. And particularly, in a high-concurrency scene, the user experience is improved.

The invention provides a resource scheduling method and system for a converged network, an intelligent terminal and a medium, and particularly relates to the technical field of network communication, and the scheme comprises the steps: carrying out the priority division and sorting of target data collected in real time according to a preset priority evaluation strategy through employing a 5G network, and obtaining the target data with the marked priority; performing time synchronization processing on all the target data marked with the priorities by using the TSN equipment to obtain the target data after time synchronization; and according to the priority and the current network state, carrying out dynamic resource allocation on the target data after time synchronization, obtaining a resource allocation result and executing a resource scheduling operation. According to the scheme, priority scheduling and a time synchronization strategy are combined based on the 5G-TSN fusion network, priority processing and accurate time synchronization of key data are ensured, the reliability and effectiveness of data transmission can be improved, bandwidth allocation is dynamically adjusted according to the data priority, and the accuracy of data resource scheduling and the data transmission efficiency can be improved.

The invention discloses a power transmission line anti-freezing system and method based on Internet of Things monitoring, and the system comprises an environmental parameter monitoring module, a data collection and transmission module, an intelligent data processing and analysis module, an early warning system module, a remote monitoring and management module, and a system management and maintenance module. Environmental parameters related to power transmission safety are collected in real time through sensors deployed at all nodes of a power transmission line, and the environmental parameters specifically comprise a temperature sensor unit, a humidity sensor unit, a wind speed sensor unit and a current load monitoring unit; environmental parameters around the power transmission line are monitored in real time through various sensors, data acquisition, transmission and processing are performed by using the Internet of Things technology, the environmental data are analyzed through an intelligent algorithm, the icing risk of the power transmission line is accurately judged, and efficient and intelligent anti-freezing monitoring comprehensive management is realized.

The invention discloses an unmanned aerial vehicle cluster intelligent formation method, device and equipment based on distributed reinforcement learning, and the method comprises the steps: constructing a reinforcement learning environment of an unmanned aerial vehicle cluster, which comprises a state space, an action space and a reward function, according to a flight task scene of an unmanned aerial vehicle, the flight mission scene comprises execution of air refueling and long-distance formation transportation; building a training framework of a distributed reinforcement learning algorithm based on the reinforcement learning environment, and performing network construction based on the training framework to obtain a neural network including an action decision network and a formation target evaluation network; performing distributed training on the neural network by adjusting hyper-parameters of the neural network and utilizing large-scale distributed data to obtain a formation model; and loading the formation model to an actual unmanned aerial vehicle cluster system, and adjusting a formation strategy according to a real-time flight environment and task requirements to carry out a formation flight task. The cooperative flight capability and the self-adaptability of the unmanned aerial vehicle cluster can be improved.

The invention discloses an artificial intelligence perioperative period anesthesia depth detection system which comprises a data acquisition module which is provided with a multi-mode sensor and is used for acquiring physiological data of a patient in a perioperative period, and an artificial intelligence model module which is used for constructing an anesthesia depth prediction model based on a deep learning algorithm. The result output and display module is used for outputting the prediction result of the anesthesia depth in real time and visually displaying the prediction result on a display screen in the form of digits and charts, and the communication and interface module is provided with an interface for data communication with a hospital information system and an electronic medical record system. By means of multi-mode collection and innovative design, the anesthesia depth detection accuracy is improved, precise monitoring and intelligent auxiliary decision making are achieved, the method can be used for various scenes, the safety of patients in the perioperative period is effectively guaranteed, and the medical efficiency is improved.

A low-altitude aircraft intelligent identification and emergency countering system relates to the technical field of low-altitude aircraft safety management and comprises a detection unit, an identification unit, a command decision platform, a scheduling unit and a countering unit. The detection unit is used for detecting all low-altitude aircrafts in a prevention and control area and obtaining flight data of all the low-altitude aircrafts; the identification unit is used for receiving the flight data and analyzing and judging the threat level of the low-altitude aircraft based on a fusion algorithm; the command decision platform is used for receiving the threat level of each low-altitude aircraft and sending a disposal instruction to the countering unit; the scheduling unit is used for giving a specific countering equipment scheduling instruction through an intelligent optimization scheduling algorithm according to the disposal instruction; the countering unit controls different countering devices to accurately strike low-altitude aircrafts with corresponding threat levels according to the scheduling instruction; according to the method, the malicious unmanned aerial vehicle can be accurately identified and can be countered in time.

The invention discloses a geographic information surveying and mapping data processing method based on image analysis, and relates to the technical field of remote sensing image processing, and the method comprises the steps: collecting a multi-angle satellite remote sensing image, and dividing the multi-angle satellite remote sensing image into a plurality of image blocks according to a geographic coordinate system; extracting topographic feature parameters of the image blocks, and establishing feature vectors of the topographic feature parameters; according to the feature vectors, establishing a ground feature classification model to perform ground feature classification on the image blocks to obtain ground feature classification labels; constructing a three-dimensional geographic information model according to the ground feature classification labels and the topographic feature parameters, and marking ground feature boundary points; and generating surveying and mapping data based on the three-dimensional geographic information model and the surface feature boundary points. According to the method, the improved three-dimensional geographic information modeling algorithm is adopted, the ground feature boundary points are precisely marked, and the problems of high ground feature classification difficulty, fuzzy boundary recognition, poor model training stability and the like in the complex terrain are effectively solved.

The invention discloses a multi-protocol adaptation method and system for a charging pile, and relates to the technical field of communication. The method comprises the following steps: acquiring communication protocol information of a target charging pile, and establishing a protocol adaptation layer; when any electric vehicle is connected to the target charging pile, reading a support communication protocol of any electric vehicle, and performing adaptive analysis with the plurality of adaptive modules to generate an adaptive result; when the adaptation result shows that the adaptation fails, connecting an intermediary adaptation module, and reading a data format of an initialized communication protocol and a data format of a supported communication protocol of the target charging pile; and converting the data format supporting the communication protocol by taking the initialization of the data format of the communication protocol as a target through the intermediary adaptation module, and performing communication between any electric vehicle and the target charging pile according to the conversion result. The technical problem that in the prior art, charging cannot be achieved due to the fact that communication protocols between charging piles and electric vehicles of different models are not compatible is solved, and the technical effect of improving the compatibility of the charging piles is achieved.

The invention relates to the technical field of power cables, in particular to a bending-resistant medium-voltage power cable, which is characterized in that a plurality of cable cores are mounted in an outer sheath at equal angles in the circumferential direction, a plurality of supporting pads are uniformly mounted in the outer sheath at equal intervals, and a protective tube is mounted in the middle of the side end surface of each supporting pad; according to the invention, equal unloading of external bending stress and external impact pressure can be realized, and internal and external dual pressure relief can be realized, so that the stress borne by each part of the cable is more balanced, and the reliability of the cable is improved. The minimum bending radius of the cable can be dynamically regulated and controlled, comprehensive regulation and control of bending toughness and bending flexibility of the cable are achieved, the requirements of different use scenes are effectively considered, the application flexibility of the cable is improved, meanwhile, the effective utilization rate of load pressure in the cable can be improved, and the effective service life of the cable is prolonged.

An interventional device for a tubular body, comprising: a stent switchable between a first state and a second state, the diameter of the stent in the second state being greater than the diameter of the stent in the first state; the at least one puncture part is arranged on the stent, and the puncture part is used for puncturing the wall of the tubular body when the stent is in the second state; the at least one electrode is arranged on the at least one puncture part, and the electrode is used for extending out of the tubular body from the area, punctured by the puncture part, of the wall. By means of the scheme, effective implantation of the electrode can be achieved based on the intervention device, the implanted electrode can make direct contact with the biological tissue target area outside the tubular body, direct and non-barrier signal interaction is achieved, and the signal collecting and stimulation applying effects of the electrode are greatly improved.

The invention relates to the technical field of digital printing machines, in particular to an intelligent ink droplet control method and system of a digital printing machine and the digital printing machine. The method comprises the steps of real-time data acquisition, multi-dimensional parameter modeling, real-time ink droplet behavior prediction, self-adaptive ink jet parameter adjustment, closed-loop feedback control, medium characteristic self-adaptive matching, intelligent multi-region optimization and environmental factor compensation. Ink droplet behaviors and environmental data are collected in real time through a high-speed camera and various sensors, a nonlinear model is constructed by using a deep learning technology, and a dynamic parameter optimization curve is generated. According to the method, the printing quality and efficiency are remarkably improved, and the method is suitable for various media and complex scenes.

The invention relates to a high-voltage cable intelligent inspection method and system based on multimode identification, and the method comprises the steps: deploying an intelligent identifier and cable monitoring equipment according to the equipment characteristics and environmental conditions in a high-voltage cable line; reading identification data of the intelligent identification through a double-frequency reading device, and collecting cable state monitoring data through a cable monitoring device; the information is uploaded to the Internet of Things cloud platform; carrying out fusion analysis on the received data in the cloud platform, evaluating the health condition of the cable in combination with a historical record and a fault recognition model, and generating an inspection result; and displaying the inspection result through the intelligent monitoring center, calculating the risk score of each device according to the identification data, the cable state monitoring data and the fault risk prediction result, and dynamically adjusting the optimal inspection route and the inspection frequency. Compared with the prior art, unique identification and multi-dimensional information storage of the cable and accessory equipment of the cable are achieved, and the fineness and comprehensiveness of cable operation state monitoring are improved.

The invention discloses a rural house structure optimization design method and system based on building information modeling, and relates to the technical field of building structure analysis design, and the method comprises the steps: obtaining geographical climate data, building user demand data and construction condition data of a to-be-built rural house; determining a house design variable set according to the acquired data; randomly generating an initial solution according to the value range of each variable parameter in the house design variables to construct an initial population; performing individual optimization on the initial population by using a genetic algorithm, screening individuals according to fitness, performing iterative genetic evolution operation including crossover and variation, and finally determining an optimal individual; and inputting target values of various variable parameters indicated by the optimal individual into a BIM construction module to determine a target BIM model for the rural house. Therefore, genetic algorithm optimization and a BIM modeling technology are organically fused, and the structural safety, the economical efficiency, the construction efficiency and the intelligent level of rural house design are improved.