143results about How to "Effective assessment" patented technology

The invention provides a multi-modal large model construction and operation method and system for reservoir dam safety. The method comprises the following steps: constructing a training set, wherein the training set comprises a single sample; multi-modal data as model input: sensor data arranged on the dam, historical hidden danger records, engineering technology documents formed in various stages of planning, design, construction and operation of the dam, information resources related to dam safety, geometric and material information of the BIM model, timestamps and spatial position information; the probability value of occurrence of the hidden danger event serving as the training label is obtained; the training set is adopted to train a multi-mode pre-training model based on a Transform framework; performing real-time prediction and early warning on potential safety hazards of the dam; and calculating the actual influence degree, the comprehensive risk score, the dynamically set early warning threshold and the emergency measure suggestion of the hidden danger event according to the probability value of whether the hidden danger event occurs or not output by the model. The scientificity and effectiveness of dam safety monitoring are comprehensively improved.

The invention provides a risk control early warning method and system based on bank flow analysis, and relates to the technical field of computers, bank flow data of a target user in a bank system is collected, the collected bank flow data is fused with multi-source cross-domain data, and time sequence data of transaction behaviors is generated according to a time sequence; performing data feature extraction on the time sequence data to obtain transaction features; constructing a framework of a risk prediction model, and obtaining the risk prediction model through training and verification; real-time flow data of a target user in a bank system is monitored in real time, a trained risk prediction model is utilized to evaluate transaction behaviors of clients in real time, an anomaly detection result of an anomaly detection model is combined with output of the risk prediction model, a comprehensive risk score is formed to identify potential risks, and an early warning mechanism is triggered. Through deep analysis of bank flow data, real-time risk monitoring and early warning are realized, and potential financial risks can be effectively identified.

The invention relates to the technical field of fault positioning, in particular to a power wire fault positioning system based on the Internet of Things, which comprises a data collection module, a fault analysis module and a data visualization module, firstly, a data collection module obtains wire data collected by a sensor on a wire in real time; secondly, the fault analysis module is used for carrying out data processing on the wire data to obtain fault data; according to the conductor data and the fault data, constructing a power conductor digital twinborn model; analyzing the fault features and the environmental parameters through a power conductor digital twinborn model to obtain an output result; analyzing the output result through a topology detection algorithm and signal sensitivity adjustment to obtain an optimized output result; obtaining a space-time propagation process formula of the fault signal through signal propagation simulation and space-time analysis according to the output result; evaluating the accuracy of an output result according to a space-time propagation process formula of the fault signal; and finally, the data visualization module generates a visualization chart and an analysis report.

The invention belongs to the field of wind power operation and maintenance, relates to a data analysis technology, and is used for solving the problem of low fault processing efficiency caused by the fact that scheduling of operation and maintenance personnel cannot be optimized in combination with an equipment operation state and a risk degree in the prior art. The intelligent management system comprises a wind power operation and maintenance platform, and the wind power operation and maintenance platform is in communication connection with a data acquisition module, an equipment operation evaluation module, an equipment risk evaluation module, an operation and maintenance grading module and a task distribution module. The equipment operation assessment module and the equipment risk assessment module assess the operation state and the risk level of the operation and maintenance equipment, and the operation and maintenance grading module and the task allocation module are used for sorting the operation and maintenance priority of the operation and maintenance equipment and the operation and maintenance capability of operation and maintenance personnel and allocating operation and maintenance tasks to the corresponding operation and maintenance personnel; the operation and maintenance task sequence and the operation and maintenance personnel sequence can be combined, scheduling of the operation and maintenance personnel is optimized, and the fault processing efficiency is improved.

The invention discloses a bridge laying high-voltage cable mechanical fatigue evaluation method and system, and relates to the field of cable fatigue evaluation. Existing methods for evaluating cable fatigue caused by factors such as bridge expansion and vibration are lacked. The method comprises the following steps: arranging a test cable on a mobile test platform, and collecting sensor data to obtain bending, stretching and compression stress of the cable; data are repeatedly acquired by moving the movable box body, and the stress condition of the cable is simulated; carrying out a slice test on the cable, and measuring the elongation at break of a cable sheath and insulation; in combination with sensor data and cable material fatigue characteristics, shape parameters and scale parameters of Weibull joint distribution are fitted, and the fatigue life, the fault probability and the mechanical failure risk of the cable are predicted based on a fitting result, so that whether the fatigue failure of the cable occurs or not is judged. According to the technical scheme, through combination of the test platform and the Weibull distribution model, the mechanical fatigue of the bridge laying high-voltage cable is accurately evaluated, and the accuracy of cable life prediction is improved.

The invention provides a structured query language evaluation method and device, equipment and a medium, and relates to the technical field of data processing, in particular to the technical field of large model and natural language processing. According to the specific implementation scheme, a query problem is obtained; generating a prediction structured query language according to the query problem by adopting a large language model; if the target structured query language exists, evaluating the accuracy of the predicted structured query language according to the predicted structured query language and the target structured query language to obtain an evaluation result corresponding to the predicted structured query language; if the target structured query language does not exist, the accuracy of the predicted structured query language is evaluated according to the semantic analysis result of the predicted structured query language, and an evaluation result corresponding to the predicted structured query language is obtained, and the accuracy of predicted structured query language evaluation is improved.

The invention provides a method for evaluating the impact force of waves on a straight wall type rock bank slope. The method comprises the following steps: S1, constructing a numerical model according to the main form of the straight wall type rock bank slope; s2, setting boundary conditions for the numerical model according to an actual marine environment; s3, selecting a numerical calculation method suitable for the interaction of the waves and the rock bank slope to set a numerical simulation program; s4, operating a numerical simulation program to simulate the stress-strain reaction of the rock bank slope under the action of waves; s5, analyzing a numerical simulation result in combination with a standard calculation result; and S6, the impact force of waves on the straight wall type rock bank slope is evaluated according to the actual working conditions. According to the method, the impact force of the wave on the straight wall type rock bank slope can be simulated and calculated by using a numerical simulation method, and the impact force of the wave on the straight wall type rock bank slope is evaluated according to a standard calculation result and an actual working condition; a more normative, effective and intuitive evaluation method is provided for evaluating the influence of waves on the stability of the rock bank slope and treating the rock bank slope to guide the actual ocean engineering construction work.

The invention provides a method for detecting the carbon coating integrity of a lithium iron phosphate material. The method comprises the following specific steps: (1) determining the conductivity sigma (S / m) of LFP powder of a sample to be detected; (2) measuring the coating layer thickness d (nm) of the LFP powder of the sample to be measured; (3) calculating the coating integrity index R of the LFP material according to the following formula: R = sigma / d; (4) the LFP material is evaluated according to the calculation result, and the larger the R value is, the better the coating integrity of the material is; according to the detection method, the carbon content and the specific surface area of the material are tested, the theoretical carbon coating layer thickness of the material can be obtained through simple mathematical calculation, the coating integrity index can be obtained by combining the result of conductivity, and a measurement standard can be provided for material integrity evaluation through clear and visual numerical values. Three different test results of the carbon content, the conductivity and the specific surface area are ingeniously integrated, evaluation is standardized by applying a simple and feasible calculation formula, and the influence of subjective factors is reduced.

The invention discloses a brain-computer interface system based on audio-visual matching error monitoring, which is characterized in that: according to EEG data obtained by three feedback paradigms of audio-visual matching errors, important ERP components related to the audio-visual matching errors are extracted by applying ERP analysis, so that neural responses in a specific time window are interpreted; then, on the basis of time-frequency analysis, dynamic changes of the electroencephalogram signals in different wave bands are captured, and the reliability and stability of the electroencephalogram activity in different feedback modes are revealed by combining ITPC of the electroencephalogram activity; and finally, through an improved EEGNet model, automatic feature extraction and efficient classification of the signals are realized, and the robustness and generalization ability of the system are improved. The electroencephalogram signals have high nonlinearity and specificity, by combining ERP analysis, time-frequency analysis and a deep learning model, potential neural mechanisms of audio-visual matching errors can be more effectively understood, the performance of a brain-computer interface system is improved, and the method is applied to clinical research of error processing related obstacles.

The invention relates to a system for predicting the concurrent coronary heart disease risk of type 2 diabetic patients and a screening kit.The system comprises an index obtaining module and a column diagram early warning module, expression levels of ESM1, BLVRA, HEXIM1 and SUMO3 are obtained through the index obtaining module, the column diagram early warning module outputs a corresponding prediction probability value according to a total score, and the larger the prediction probability value is, the higher the coronary heart disease risk is. The method can evaluate the risk of the current patient suffering from coronary heart disease, can screen early patients suffering from type 2 diabetes patients suffering from coronary heart disease in combination with a coronary heart disease diagnosis technology, and is beneficial to timely and effectively control the progress of coronary heart disease and reduce the disability and fatality rate.

The invention discloses a water and soil conservation soil loss data monitoring system and method, and the method comprises the steps: constructing a soil loss data management container through a water and soil conservation management device according to the information of a to-be-monitored target region, the soil loss data management container divides the to-be-monitored target area into a plurality of sub-areas of the monitored target area; the soil loss data management container creates soil loss data management sub-containers corresponding to the water and soil conservation monitoring features according to the sub-region sequence of the monitoring target region corresponding to the water and soil conservation monitoring features; and the soil loss data management sub-container corresponding to the water and soil conservation monitoring characteristics obtains a data sequence and a data change trend corresponding to the water and soil conservation monitoring characteristics according to the sub-region sequence of the monitoring target region corresponding to the water and soil conservation monitoring characteristics, and completes water and soil conservation monitoring of the to-be-monitored target region.

The invention relates to a space-ground consistency evaluation method for average pressure in a rocket interstage separation pressure building process. The method comprises the following steps: for the rocket interstage separation pressure building process, calculating pressure rising speeds of a temperature rising section and a temperature stable section of an engine flight test state; under the determined detonation gas product total enthalpy condition, the product of the outlet section flow and the total enthalpy is close to the flight test state, and the outlet flow required by the test is obtained; according to the outlet flow, the pressure rising speed of the rocket engine ground simulation device in the pressure building process is evaluated, and it is confirmed that the difference between the pressure rising process of the ground simulation device and the flight test state is within the engineering application deviation requirement; evaluating the working environment of the ground simulation device; and evaluating the over-assessment degree of the pressure rising speed of the ground simulation device in the pressure building process compared with the flight test state. Flight state equivalent simulation of an internal environment and an external environment in a ground test scheme is realized, so that the ground test can reasonably verify a real pressure building process of inter-stage thermal separation in a multi-stage rocket flight test.

The invention discloses an evaluation method for nutrition management of a large language model. The method comprises the following steps: constructing an evaluation data set; submitting problems in the assessment data set to a to-be-assessed large language model; collecting answers of the big language model for the question, and classifying the answers according to the content of the answers; calculating the answer accuracy of the large language model according to the classification; the method relates to the technical field of big language model evaluation, reduces the influence of human factors and improves the objectivity and reliability of an evaluation result by constructing an evaluation data set and setting a clear evaluation standard, covers a plurality of aspects of nutriology, and has the advantages that the evaluation data set is established, the evaluation standard is set, the evaluation accuracy is improved, and the evaluation efficiency is improved. Comprising multiple dimensions of food and nutriology, individual and group nutrition management, public nutrition and nutrition education, diet management and the like, and the comprehensive ability of the large language model in the field of nutriology can be comprehensively evaluated.

The invention belongs to the technical field of photovoltaic adhesive film packaging defect detection, and particularly relates to a photovoltaic adhesive film packaging defect test method which comprises the following steps: step 1, packaging a photovoltaic adhesive film on a photovoltaic cell according to a preset packaging process to prepare a test sample; 2, performing infrared thermal imaging detection on the test sample to obtain infrared thermal imaging data of the test sample, performing digital image processing on the infrared thermal imaging data, and judging whether packaging defects exist or not; if the packaging defect exists, the position and the range of the defect are further determined, and otherwise, the test sample is output as a qualified product; 3, performing ultrasonic detection on the test sample with the packaging defect, and outputting an ultrasonic detection result; and 4, evaluating and analyzing the packaging defects of the photovoltaic adhesive film. According to the invention, two methods of infrared thermal imaging detection and ultrasonic detection are combined, so that packaging defects can be detected more comprehensively and accurately; and the detection accuracy and efficiency are improved.

The invention provides a text clustering system for open source security intelligence. The text clustering system comprises a data acquisition module, a preprocessing module, a feature extraction module, a similarity calculation module, a clustering initialization module, an iterative clustering module, an evaluation module and a result output module. The system collects a target text, removes noise, calculates a word frequency and an inverse document frequency to construct a feature vector, calculates similarity after normalization processing, randomly selects an initial clustering center, iteratively updates the clustering center until the clustering center is stable, evaluates a clustering effect, outputs a clustering result and generates a topic tag. According to the invention, the analysis efficiency and accuracy of open source security intelligence can be improved, and security threats can be quickly identified and responded.

The invention relates to the technical field of charging pile state evaluation, in particular to a charging pile state evaluation method, which adopts a signal conditioning function, enhances signal strength, removes noise and interference, can comprehensively obtain weak signals of an output interface of a charging pile, and uses a time domain and frequency domain analysis algorithm to evaluate the state of the charging pile. Discrete sampling and fast Fourier transform are accurately carried out, so that a voltage effective value and a current effective value are accurately calculated, a signal spectrogram is accurately obtained, harmonic related indexes are accurately calculated, a charging pile electrical performance evaluation system is established, the influence of multiple factors on the electrical performance of a charging pile output interface is comprehensively considered, and the evaluation accuracy is improved. The state of the charging pile is effectively evaluated, the state of the charging pile is accurately obtained, potential problems can be found in time by accurately evaluating the state of the charging pile, powerful support is provided for maintenance and management of the charging pile, the maintenance efficiency of the charging pile is improved, and manpower and time cost is saved.

The invention belongs to the field of satellite remote sensing application, and particularly relates to a rapid mapping method for soil organic matter distribution, in particular to a rapid mapping method for 16m-resolution soil organic matter distribution of a Gaofen-1 satellite. The invention aims to solve the problems that the soil fertility condition of farmland cultivated land is reduced and the cultivated land quality is degraded. The method comprises the following steps: acquiring different wave band remote sensing reflectivity of a Gaofen-1 satellite WFV sensor in a target research area; remote sensing reflectivity and remote sensing reflectivity wave band combinations of different wave bands of WFV sensor images are used as input variables of a random forest algorithm, output variables are cultivated land surface soil organic matters (mg / g), and cultivated land surface soil pH mapping is achieved. Based on a domestic Gaofen-1 satellite WFV sensor, the method provided by the invention can realize dynamic monitoring of the cultivated land surface soil organic matters, and actual measurement sample point verification finds that the method provided by the invention can accurately estimate the cultivated land surface soil organic matters, and is beneficial to management in aspects of soil fertility condition monitoring, precision agriculture and land sustainable utilization.

The invention discloses a dynamic stiffness performance analysis method for an all-in-one motor assembly for a vehicle, sub-components of the all-in-one motor assembly comprise a controller upper cover plate, a controller lower cover plate and a rotary transformer cover plate, and the method comprises the following steps: 1) carrying out frequency domain response tests on the sub-components of the all-in-one motor assembly; 2) modal frequency identification of each sub-component of the all-in-one motor assembly; 3) performing frequency domain response test on each suspension mounting point of the all-in-one motor assembly; 4) calculating the dynamic stiffness of each suspension mounting point of the all-in-one motor assembly; 5) performing a frequency domain response test of the all-in-one motor assembly; 6) identifying the modal frequency of the all-in-one motor assembly; and 7) calculating and analyzing the rigidity performance of the all-in-one motor assembly. According to the invention, rapid iteration of the all-in-one motor assembly can be realized on the premise of no rack and whole vehicle resource support; the purposes of shortening the development period, recognizing risk problems in advance and saving the test cost of the whole vehicle are achieved.

The invention discloses an external rotor permanent magnet synchronous motor noise prediction method, system and device and a medium, and relates to the technical field of motor noise, and the method comprises the steps: building a two-dimensional electromagnetic model of an external rotor permanent magnet synchronous motor ERPMSM; analyzing the spatial distribution and frequency characteristics of the electromagnetic force acting on the surface of the permanent magnet through the two-dimensional electromagnetic model to obtain the electromagnetic force; establishing a three-dimensional structure model of the ERPMSM, and loading the electromagnetic force into the three-dimensional structure model in a nodal force form to obtain a nodal force acting on the surface of the permanent magnet in a three-dimensional space; based on the three-dimensional structure model and the nodal force, the radial vibration acceleration of the ERPMSM outer rotor is calculated by adopting a mode superposition method; and taking the radial vibration of the outer rotor as an acoustic boundary condition, and predicting the noise of the ERPMSM by using an acoustic boundary element method.

The invention discloses an agricultural voice question answering system based on large model reasoning and intelligent auxiliary error correction, which relates to the technical field of agricultural knowledge intelligent question answering and comprises a robot terminal interaction module, a user interaction layer, a question answering processing layer, a performance evaluation optimization module and a data layer. According to the method, the GPT large model based on the Transform architecture is utilized, agricultural field adaptation is carried out, the powerful language understanding and generating capacity of the large model can be fully utilized, agricultural related problems can be better processed after fine tuning, initial answers with certain accuracy are generated, a powerful knowledge source and an inference engine are provided for the system, and the system has good application prospects. According to the method, the initial answer generated by the large model can be effectively evaluated and corrected by learning the characteristic difference of a large number of agricultural question and answer data pairs in cooperation with the established BERT error correction model, so that the accuracy and reliability of system answers are improved, and wrong answers possibly occurring in the large model are reduced.

The invention discloses a mangrove forest information drawing method and system cooperating with SAR and optical remote sensing data. The mangrove forest information drawing method comprises the steps that an SAR image, an optical image and digital elevation model (DEM) data of a target research area are acquired; based on the SAR image and the optical image, obtaining image fusion features, index features, texture features and polarization features of the target research area ground features; carrying out importance sorting on all the obtained features, and sequentially adding the features into a machine learning model according to a sequence from high to low to carry out distinguishable analysis on ground features; selecting a sample based on the high-resolution image, and training an established machine learning model for mangrove forest extraction based on the sample to determine a mangrove forest extraction model; and extracting mangrove forest information in the target research area based on the mangrove forest extraction model, and screening the mangrove forest area in combination with DEM data so as to complete mapping of the mangrove forest information.

The invention discloses a training teaching management analysis system and method based on big data, relates to the field of big data, solves the problem that the training success of a to-be-trained person cannot be effectively evaluated, and comprises a training planning module, a training plan management module, a training evaluation module, a physical fitness assessment module and a comprehensive evaluation module. The training planning module is used for planning the training plan to obtain a final training plan; the training plan management module is used for managing the training plan to obtain the daily completion condition of the training plan corresponding to the to-be-trained person; the training evaluation module is used for evaluating the training condition of the to-be-trained person to obtain a training assessment score value; the physical fitness assessment module is used for assessing the physical fitness condition of the to-be-trained person to obtain a physical fitness score value; the comprehensive evaluation module is used for comprehensively evaluating the training result of the to-be-trained person to obtain the comprehensive training grade of the to-be-trained person, and effective evaluation of the training result of the to-be-trained person is achieved.

The present invention relates to the field of photocatalyst detection technology, and specifically to a photocatalyst degradation performance detection system and method, the system comprising a detection unit, the detection unit being provided with an inlet and an outlet, the outlet and the inlet of the detection unit being provided with a pollutant concentration detection module, the pollutant concentration detection module being used to detect the concentration of pollutants passing through; and also comprising a processing module, the processing module being used to obtain and record pollutant concentration data detected by the pollutant concentration detection module, control the operation of an ultraviolet light source component, a driving component and a temperature control component, and calculate the pollutant degradation performance of the photocatalyst under multiple groups of different lighting conditions and different detection environment temperature conditions. The present invention can synchronously obtain the pollutant degradation performance results of multiple groups of photocatalysts under different lighting conditions and different detection environment temperature conditions. The convenience of photocatalyst degradation performance detection and the efficiency of photocatalyst degradation performance detection are improved.

The invention discloses a risk assessment method and device based on user psychological assessment data, and the method and device can timely obtain a current feedback data set for psychological assessment of a student user, an emotion recognition result corresponding to a test process video data set, a current student user course data set, and a current student user test score data set. And multi-dimensional data of the student user is effectively combined for classification and evaluation, so that a current classification output result which is high in real-time performance and is more visually and quantitatively displayed is obtained, and a teacher user of the psychological health major can view and analyze the result.

The invention relates to PLC (Programmable Logic Controller) detection, in particular to a PLC test system, which comprises an upper computer, and is characterized in that a corresponding test scheme is screened out from a pre-stored test scheme library according to a test requirement, a corresponding test process is acquired from the test scheme, and the test process is issued to a lower computer; the lower computer determines corresponding test steps according to the test process issued by the upper computer, controls the to-be-tested PLC to execute the test steps by sending an input signal to the to-be-tested PLC, and evaluates a PLC network environment according to the input signal and an output signal sent by the to-be-tested PLC; the to-be-tested PLC executes testing steps under the control of the lower computer and sends an output signal to the lower computer at the same time; the interference source is used for applying an interference signal to a network environment between the lower computer and the PLC to be tested; according to the technical scheme provided by the invention, the defect that the PLC is difficult to efficiently and comprehensively test in the prior art can be effectively overcome.

The invention relates to the technical field of information management, and discloses a human resource information digital management method and system based on big data. Firstly, human resource data index scores in the original human resource data matrix are calculated by using a principal component analysis method, and executive ability values of employees are calculated after principal components are screened; secondly, classifying the employee execution capability values by using an improved clustering algorithm, and introducing a particle swarm optimization algorithm to search an optimal initial clustering center so as to complete position distribution; training a BP neural network to obtain a BP neural network model, predicting employee performance, and outputting an employee performance prediction value; and finally, performing employee performance assessment and evaluation according to the employee performance predicted value, thereby realizing digital management of human resource information. By analyzing and processing the human resource data, the purpose of human resource information digital management is achieved, and the method is objective and accurate.

The invention discloses a damp cable joint degradation state detection system and method based on multi-characteristic quantity acquisition, and the method comprises the steps: S1, packaging a cable intermediate joint in a gas sampling bag, and enabling a grounding wire of a cable to be grounded; s2, providing a preset test voltage for the cable through a power supply adjusting device and keeping the preset test voltage unchanged; s3, continuously electrifying, detecting discharge signals of the cable body and the grounding wire through a discharge characteristic acquisition device, and carrying out online monitoring and analysis; s4, opening a gas valve of a gas extracting pump to extract gas when a discharge signal with a remarkably changed waveform is monitored, and analyzing the components and content of the characteristic gas through a gas chromatograph; s5, identifying, extracting and analyzing the discharge signal after acquisition is completed to obtain an effective discharge waveform; and S6, comprehensively analyzing the result, and evaluating the degradation state of the cable intermediate joint. The method can effectively evaluate the deterioration state of the intermediate joint of the damped cable, and is high in reliability.

The invention provides a video code stream quality evaluation method, which comprises the following steps of: for each frame image in a video code stream, performing macro block decoding on the frame image to obtain a plurality of macro blocks; in the macro block decoding process, determining the type of an error macro block aiming at the error macro block generated by the macro block decoding information error; determining the number of center error macro blocks of the frame image, and evaluating the quality of the frame image at least according to the number of the center error macro blocks of the frame image and the total number of the macro blocks; according to the embodiment of the invention, by evaluating the quality of the video code stream at the macro block level, the unit of quality control can be reduced from the current coding fragment to the macro block level, so that the decoding process can be controlled more finely, and the decoding and display effects can be improved; and the quality of the frame image can be quickly and effectively evaluated based on the central error macro block at the central position of the frame image. The invention further provides computer equipment and a readable medium.

The invention discloses a lightweight class attention mechanism fused improved YOLOv7 flame detection method and system. The method comprises the following steps: acquiring flame and non-flame images, preprocessing the flame and non-flame images, constructing a flame detection data set based on the preprocessed flame and non-flame images, and labeling and dividing the flame detection data set; the original YOLOv7 network model is optimized, and an improved YOLOv7 network model is obtained; training the improved YOLOv7 network model by using the training set, and adjusting model hyper-parameters by using the verification set in the training process to obtain a flame detection model; evaluating the performance of the flame detection model by using the test set; and deploying the flame detection model in a monitoring camera of the power distribution station, and carrying out real-time monitoring and alarming on flames in the power distribution station by using the model. The technical problem that in the prior art, light weight and detection precision of a model are mutually balanced, and actual application requirements are not easy to meet can be solved.

The invention provides a rural digital twin photovoltaic energy management method and system based on the Internet of Things, and the method comprises the steps: carrying out the grid division of a rural photovoltaic energy region, and obtaining all grid points; constructing a minimum working area of each grid point based on the minimum working size and the corner of the photovoltaic panel, and screening out effective areas to form a set; establishing a corresponding relation between the minimum working area and the grid points; constructing an illumination area and a probability matrix; and taking each grid point as an energy management point, and finding out an optimal energy management point by updating an energy output probability and calculating a connection weight sum. According to the invention, the efficiency and accuracy of photovoltaic energy management can be improved.