1133results about How to "Reduce management costs" patented technology

The invention belongs to the technical field of electric power data security management and intelligent question answering, and particularly relates to an electric power data security policy large model question answering system and method based on relation pooling. The system comprises a power data security policy knowledge base, a language model, a question processing module, an answer generation module and a user output module. Data of the electric power data security policy knowledge base comes from an electric power data security policy file; the language model converts a natural language problem into a structured query for knowledge base retrieval; the question processing module retrieves policy terms related to the natural language question to serve as retrieval results; the answer generation module generates a final answer according to the natural language question and a retrieval result of the knowledge base; by introducing the intelligent question-answering system combining the large language model and the knowledge base, the problems of low efficiency, inaccurate interpretation, incapability of dynamically updating and the like in the existing power data security policy query and management are solved.

The invention discloses a virtual power plant system design method based on multilevel federated learning, and relates to the technical field of power system planning, and the design method comprises the steps: designing and constructing a virtual power plant system architecture comprising an energy resource module, a local controller, a regional coordinator, a central coordinator and a regional block chain network. Intelligent prediction and optimal control of distributed energy resources are realized by using a deep learning framework and a model training algorithm, the intelligent level of the system is improved, automatic management of energy transaction and execution of an intelligent contract are realized by using a block chain technology, transparency and security of the transaction are ensured, and multi-level federated learning is adopted, so that the efficiency of the system is improved. According to the invention, distributed cooperation of data distributed processing and model training is realized, risks of data leakage and privacy invasion are effectively avoided, cooperative work of a local controller and a regional coordinator is cooperated, intelligent management and optimal scheduling of distributed energy resources are realized, and manual intervention and management cost are reduced.

The invention provides a containerized micro-service intelligent collaborative orchestration method and device, and the method comprises the steps: determining a service completion time delay index of a micro-service architecture system, determining a system load balancing index according to the environment information of the micro-service architecture system, and carrying out the orchestration training of an initialization orchestration model according to the index, and obtaining a micro-service orchestration model; inputting the obtained request state information corresponding to the user service request into a micro-service arrangement model for strategy arrangement processing to obtain an arrangement strategy; and deploying the containerized micro-service according to the arrangement strategy, and operating the deployed containerized micro-service to process a user service request. Through application of the method and the device, the technical problems of low service performance of the micro-service architecture system and increased management cost caused by difficulty in balancing two indexes of service completion time delay and system load balance in the micro-service architecture system when the containerized micro-service is arranged by adopting a scaling method in the prior art are solved.

The invention discloses an in-tunnel construction vehicle meeting scheduling system based on positioning equipment. The system comprises a basic service module which is used for storing basic data for business service analysis in an acquisition and collection mode; the business service module is used for carrying out detailed analysis of the corresponding service through the data acquired by the basic service, and providing an analysis result to the display end for display; and the display end module is used for displaying the analysis result of the business service module, wherein the display modes comprise a mobile phone APP, a webpage large screen, an LED panel, a tunnel loudspeaker and a tunnel traffic light. The system carries out weight grading on vehicle and personnel positioning labels by standardizing a tunnel construction process, and integrates data of avoidance points of a transverse tunnel. And in combination with an intelligent technology, efficient vehicle meeting scheduling, intelligent construction path planning and avoidance point path planning of the construction area are realized.

The invention relates to the field of data asset management, and discloses a DCMM-based data asset active management method and system, and the method comprises the following steps: collecting data assets from all business systems, extracting multi-dimensional features, and generating a data attribute matrix; constructing a data value quantification model, and calculating the value of each data asset; based on a multi-objective optimization model, data assets are subjected to classification management, and optimization balance of data value, security, access efficiency and storage cost is realized; dynamically adjusting the weight of an optimization target according to different levels of the DCMM to enable a data management strategy to adapt to the data management maturity requirement of an enterprise; and performing resource allocation and priority control on the data assets according to an optimization result to realize active management. According to the method and the system, the accuracy, the flexibility and the resource utilization rate of data asset management are improved, and optimal configuration and efficient management of data assets in different development stages of enterprises are facilitated.

The invention discloses a photovoltaic power station management method and system based on artificial intelligence and big data analysis, and relates to the technical field of photovoltaic power generation. The photovoltaic power generation group comprises a plurality of photovoltaic group strings used for connecting a plurality of photovoltaic panels, at least one combiner box, a direct current cable, a central inverter and an alternating current cable; according to the method, the running state of a photovoltaic power generation set is monitored in real time, abnormal conditions are rapidly recognized based on comparison of predicted power generation capacity and first photovoltaic power generation capacity, faults are subjected to hierarchical management through a comprehensive fault evaluation index, a proper rectification scheme is matched, in addition, the state of a photovoltaic panel is subjected to nondestructive testing through visible light and infrared imaging technologies, and the reliability of the photovoltaic power generation set is improved. According to the method, meteorological data and historical operation parameters are combined, fault reasons and damage degrees are comprehensively evaluated, fault data are updated and uploaded to a photovoltaic data platform after maintenance is finished, model performance is optimized, and the management method improves response speed, reduces fault processing time and reduces maintenance and management cost.

The invention discloses an edge-end-side heterogeneous computing power resource scheduling system and method.The system comprises a computing power virtualization resource pool module, a cross-domain distributed computing power soft bus and a computing power resource scheduling management module, the computing power virtualization resource pool module is based on the heterogeneous computing power virtual computing resource pool technology, and the cross-domain distributed computing power soft bus is used for scheduling the computing power resource scheduling management module; performing unified management and virtualized mapping on various equipment systems on the edge side and the end side according to computing power resources, network resources and storage resources to form a unified virtual computing resource pool; according to the cross-domain distributed computing power soft bus, intermediate routing forwarding nodes of computing power resources are established among different communication domains, the routing forwarding nodes support a power system physical layer protocol, and computing power resource lists among different communication protocol networks are synchronously updated in real time; and the computing power resource scheduling management module is used for realizing dynamic allocation management of computing power resources based on a dynamic computing power scheduling system established by the computing power resource pool, evaluating the computing power demand required by each computing task in real time, and requesting the virtual computing resource pool to allocate an optimal computing power resource combination for algorithm application.

The invention discloses a data asset management method based on a knowledge graph, and relates to the technical field of data processing and data management.The data asset management method based on the knowledge graph comprises the steps of data collection and preprocessing, knowledge graph construction, data source integration, data asset management and intelligent recommending.The data asset management method based on the knowledge graph has remarkable advantages; comprising the steps of improving the utilization rate and safety of data assets, simplifying the management process of the data assets, reducing the management cost, and supporting intelligent decision and good expandability and customizability. The method is suitable for various scenes needing to manage a large amount of data, and an efficient and intelligent data asset management solution is provided for enterprises.

The invention discloses a BIM-based whole house intelligent control system. The system is mainly formed by mutual cooperation of a BIM model data integration unit, an Internet of Things access unit, a control and management unit, an energy consumption analysis and optimization unit and a user interaction and platform integration unit. The invention provides a BIM-based whole house intelligent control system, and the system achieves the deep fusion of a BIM model (a building information model) and intelligent household equipment (i.e., Internet of Things equipment), thereby achieving the bidirectional data interaction between the BIM model and the household Internet of Things equipment, achieving the equipment management, energy consumption optimization, automatic control and remote operation and maintenance, and achieving the intelligent control of the whole house. And the living experience of the user and the equipment management efficiency are improved.

The invention discloses an automatic DCMM evaluation system based on a multi-source heterogeneous data integration mechanism, and relates to the technical field of data quality management.The automatic DCMM evaluation system comprises a data source management module, a data integration module, a data quality evaluation module, a data quality diagnosis module and a data quality monitoring module which are connected through electric signals; and the data source management module is used for accessing various types of data sources and collecting original multi-source heterogeneous data from a plurality of data sources. By comprehensively monitoring and evaluating the data quality, the accuracy and integrity of the data are improved, the abnormal early warning coefficient is calculated, the potential data quality risk is recognized in time, and when it is detected that the data quality is abnormal, an early warning mechanism is automatically triggered, and an alarm is sent to inform related personnel, so that the data quality is ensured to be abnormal. Therefore, the data quality problem can be found and solved at the first time, so that the reliability and credibility of the data are improved.

The invention discloses an energy storage cabinet temperature control method based on a cloud platform and a temperature control energy storage cabinet, and relates to the technical field of electric energy storage, the energy storage cabinet comprises a cabinet body, an energy storage module, a data acquisition module, a communication module and a temperature control module, and the temperature control method comprises the following steps: S1, acquiring environmental parameters and battery state data; s2, determining a temperature adjustment factor of the energy storage cabinet through the battery state data; s3, generating a composite temperature index based on the environmental parameters and the temperature adjustment factor; s4, performing region division on the energy storage cabinet, determining temperature requirements of different regions according to the composite temperature index, and formulating an energy storage cabinet temperature control strategy based on the temperature requirements in combination with the environment prediction temperature; s5, the cloud platform generates a control instruction based on the temperature control strategy and issues the control instruction to the energy storage cabinet to execute the control instruction; accurate control over the temperature in the energy storage cabinet can be achieved, it is ensured that energy storage equipment operates within the optimal temperature range, the energy storage efficiency is improved, and the service life of the equipment is prolonged.

The invention discloses a method and equipment for rapidly and continuously preparing carbon nano tubes with adjustable tube diameters, which are used for continuously and rapidly preparing carbon nano tubes with different tube diameters and at least comprise a catalyst precursor atomizing chamber, a plasma device, a carbon nano tube preparation reactor, a collector and a tail gas treatment device. A catalyst precursor solution enters the atomizing chamber through the injection pump to be atomized, atomized mist enters the plasma treatment device and then enters a reaction from a sample inlet in the upper portion of the reactor, after the reaction in the reactor is completed for a short time, the carbon nanotubes are collected from a collecting device on the lower portion of the reactor, and tail gas can be returned to the reactor after being filtered by the filter. The tail gas can be repeatedly used; and the continuous preparation of the carbon nano tubes with different tube diameters can be realized.

The invention discloses a city appearance environment early warning method and system based on AI intelligent garbage identification, and relates to the technical field of artificial intelligence and garbage classification technologies. The method comprises the steps that firstly, garbage classification throwing stations are set; step 2, acquiring and processing image data; step 3, carrying out image frame selection and tracking; 4, setting a threshold value and generating prompt information; 5, scheduling the garbage trucks, connecting the garbage trucks in series according to the uploaded alarm stations, and designing a route; by monitoring the state of the garbage throwing station in real time, the system can timely find the situation that the number of the garbage cans reaches the standard, and automatically generate early warning information, so that an environmental sanitation management department can timely dispatch garbage trucks to carry out clearing and transportation, and environmental pollution and resource waste caused by long-time garbage accumulation are avoided; the dynamic adjustment function of the system ensures that the driving route of the garbage truck can be rapidly updated when the actual situation changes, for example, early warning is newly added, and the garbage treatment efficiency and the response speed are further improved.

The invention relates to the technical field of material storage management, in particular to a BIM-based construction site material monitoring management method and system. The method comprises the following steps: obtaining a construction project drawing; performing drawing information extraction on the construction project drawing to obtain construction project material information data and construction project structure data; performing construction project three-dimensional modeling on the construction project material information data and the construction project structure data to generate construction project three-dimensional modeling data; obtaining total construction material data; and carrying out material information modeling on the total construction material data by using a BIM technology to generate total construction material modeling data. According to the invention, accurate three-dimensional modeling, intelligent marking, regionalized storage and real-time allocation of the construction site materials are realized through the BIM technology, and the accuracy of construction site material monitoring management and the emergency response real-time performance are improved.

The invention provides an intelligent guard system for large-scale micro-nano processing laboratory equipment, and the system comprises a data collection module, a risk early warning module, a fault positioning module and an operation and maintenance management module, the fault is traced by using the collected real-time environment data, real-time state data, experimental data, real-time behavior data and identity information, so that the details of the fault can be known in time, and fault maintenance, responsibility investigation and the like can be carried out; the operation and maintenance management module can carry out multi-dimensional operation and maintenance management on the laboratory according to the collected real-time environment data, real-time state data, experimental data, real-time behavior data and identity information, so that the efficiency, the performance and the service life of equipment are improved, the maintenance cost of the equipment is reduced, and effective utilization of social resources is facilitated.

The invention provides a staple food grain crop disease grading method and system based on a prompt-driven large model, and the method comprises the following steps: collecting and preprocessing a main food crop image, and obtaining a main food crop data set; training a ResNet-18 network based on the main grain crop data set to perform initial disease grading, and obtaining disease characterization prompt information; utilizing disease characterization prompt information to drive a prompt drive large model, and segmenting a focus area and a leaf area of the to-be-graded main grain crop image; and calculating the proportion of the lesion area in the leaf area, obtaining a final fine-grained disease grading result of the to-be-graded main grain crop image, and completing staple food crop disease grading based on the prompt-driven large model. According to the method, automatic detection and grading of crop diseases are realized by integrating deep learning and an interactive segmentation technology, so that the accuracy of disease detection and classification is improved, possibility is provided for optimizing the use of pesticides, and environmental pollution and the risk of crop drug resistance are reduced.

The invention discloses a well station instrument fault intelligent diagnosis system and diagnosis method based on big data and artificial intelligence, and the system comprises a well station instrument data management and acquisition module which collects and stores well station instrument data in real time, and provides a visual data display interface at the same time, so that an operator can know the operation state of a well station in time; the well station instrument data analyzing and processing module is used for analyzing the collected well station instrument data and extracting key index data; according to the well station instrument fault early warning model system, a multi-level early warning model is created, and potential faults of well station instruments can be effectively recognized and predicted; and the well station instrument fault diagnosis and analysis module is used for quickly identifying abnormal conditions in the well station instrument data, making fault early warning and analysis reports and providing the fault early warning and analysis reports to management personnel. According to the intelligent diagnosis system and the diagnosis method, problems possibly occurring in production are analyzed and predicted through an intelligent algorithm and a model, and corresponding measures are taken in advance so as to ensure safety and stability of oil well production.

The invention provides a factory production intelligent management system based on a large language model, and is suitable for the field of factory production management systems. The system comprises a gateway module, a system management module, an ERP docking module, a production management module, a task scheduling module, a file management module, an authority authentication module, a logistics management module and a multi-factory management module. Corresponding module logs and large language model analysis functions are added to the gateway module, the system management module, the ERP docking module, the production management module and the task scheduling module, and the functions of dynamically updating flow filtering rules and intrusion detection are realized in a service hot deployment mode to cope with continuously evolving production environment and system security threats. Parameter configuration is dynamically adjusted in a hot loading mode to solve problems occurring in a system management log, a large amount of customized development and maintenance work is reduced in the docking process with an ERP system, a production plan is automatically adjusted in the production management process, and optimal resource allocation is obtained.

The invention provides a safety management and control system for an intelligent lock of a transformer substation, and the system comprises an intelligent wearable device which is used for monitoring the physiological data of a wearer in real time; the environment monitoring module is used for monitoring the environment risk of the working area in real time; the video monitoring module is used for monitoring the in-out dynamic state and the behavior standard of the personnel; the intelligent lock linkage management module is used for automatically locking an intelligent lock and giving an alarm according to monitoring results of the intelligent wearable device, the environment monitoring module and the video monitoring module when abnormity is monitored; the risk assessment module is used for establishing a risk assessment model and dynamically adjusting the operation authority of the intelligent lock; and the situation awareness control module is used for changing the operation authority of the intelligent lock according to the situation evaluation result. The invention further discloses a corresponding method. According to the invention, the safety and management efficiency of electric power facilities such as a transformer substation are improved.

The material carrying device comprises a transplanting trolley and a positioning assembly used for positioning the transplanting trolley, a tray is movably arranged on the transplanting trolley, and a tray positioning part is arranged at the position of the positioning assembly; the number of the positioning assemblies is two, a channel for the transplanting trolley to pass through is formed between the two positioning assemblies, each positioning assembly comprises at least one positioning mechanism, and the transplanting trolley is provided with a positioning limiting mechanism matched with the positioning mechanism; the two tray positioning parts are located on the two sides of the channel, each tray positioning part comprises a jacking assembly which is vertically arranged in a sliding mode, according to the scheme that the AGV is used for carrying PACK production line materials, the flexibility of the flow direction of the production line and the completion sequence of completion procedures is improved, and the process sequence and unqualified product treatment are more flexible; the AGV moves on the road surface, no track is needed, maintenance is convenient, and cost is low.

The invention discloses an employee work ability assessment method based on multi-modal health data fusion. The method comprises the steps of obtaining a plurality of health index values of physical examination data of an employee to be assessed, a plurality of self-assessment scale scores of psychological assessment data and a plurality of physiological monitoring index values of wearable device data; performing standardization processing on the acquired data, and converting the standardized data into feature vectors respectively; respectively inputting the feature vectors corresponding to the physical examination data and the psychological evaluation data into a trained multi-layer perceptron for feature extraction to obtain a physical examination feature vector and an evaluation feature vector; inputting the feature vector of the wearable device data into a trained long-short-term memory network for feature extraction to obtain a wearable feature vector; and inputting the physical examination feature vector, the evaluation feature vector and the wearing feature vector into a fusion module of a trained multi-modal learning model to perform feature fusion, and inputting the fused features into a DNN model of the multi-modal learning model to generate a work ability score.

The invention discloses an internal medicine laboratory data sharing and querying system, and relates to the technical field of laboratory data security sharing. A special management and control terminal is arranged to match internal medicine laboratory data of a corresponding patient according to identity information of a pre-queried patient; according to the method, the preset security conversion rule is used for converting the internal medicine laboratory data to obtain the corresponding shared query data, so that the dependence on a key is eliminated, the management cost of the key is saved, and the management difficulty is reduced; in the process of converting the internal medicine laboratory data, the internal medicine laboratory data is intercepted through the preset intercepted character quantity, whether each character in the intercepted data is 8 or 9 or not is judged, a plurality of grouped word strings are intercepted and selected based on judgment, and then the corresponding shared conversion sequence is obtained, so that the security of the data is improved, and the conversion efficiency of the internal medicine laboratory data is improved. And a safer and more reliable guarantee is provided for sharing and querying of internal medicine laboratory data, and the privacy of patients and the safety of medical data are ensured.

The invention discloses a financial sharing center receivable and payable integration method and system and a storage medium thereof.The financial sharing center receivable and payable integration method comprises a receivable method and a payable method, and the receivable method comprises the steps that receivable information is formed in a heterogeneous system; the receivable information at least comprises an order with customer information, delivery information and an invoicing notice; the heterogeneous system calls an interface of the financial sharing center and pushes receivable information to the financial sharing center; carrying out standardized auditing on receivable business through the financial sharing center; and if the audit is passed, the financial sharing center is connected with a tax system to perform invoicing and ticket processing, and after the audit is passed, the heterogeneous system calls the financial sharing center to obtain receivable business data after the business of the financial sharing center is completed, and a general ledger is formed for accounting and archiving. According to the invention, the whole receivable and payable process is automatic from the links of order generation, fund collection, accounting check, invoice management, supplier payment and the like.

The invention discloses a data annotation method based on a large model. The data annotation method comprises the following specific steps: acquiring data and preprocessing the data to obtain input data; performing model training based on the arbitrary-degree large model and the input data to obtain a pre-trained arbitrary-degree large model; performing interface packaging on the pre-trained random degree large model; performing fine tuning on the packaged pre-training arbitrary-degree large model to obtain a target arbitrary-degree large model; acquiring to-be-labeled data, inputting the to-be-labeled data into the target arbitrary-degree large model for labeling, and outputting to obtain labeled data; and monitoring, feeding back and recording the fine tuning process of the pre-trained arbitrary-degree large model and the labeling process of the target arbitrary-degree large model to obtain historical fine tuning data, historical data to be labeled and historical labeling data. According to the method, the problems of label imbalance, label inaccuracy and image label error are solved, the labeling quality and efficiency are improved, and the labeling cost is reduced.

The utility model discloses a rotor structure of a permanent magnet auxiliary reluctance motor, which comprises a rotor punching sheet, a plurality of magnetic steel groove groups are fixedly arranged on the rotor punching sheet, each magnetic steel groove group consists of a plurality of layers of magnetic steel grooves, corresponding magnetic steel bodies are arranged in the magnetic steel grooves, the magnetic steel bodies are rectangular, and the magnetic steel bodies are rectangular. The rotor punching sheet is used for a permanent magnet auxiliary reluctance motor with the rotor punching sheet, the motor is provided with a multilayer magnetic steel structure, large reluctance torque can be obtained, for a rotor with N layers of magnetic steel grooves, the types of magnetic steel can be reduced from 2N-1 to N, 2 or 1, the types of magnetic steel can be reduced, and the purchase, production and management costs of the motor can be reduced.

The invention discloses an express delivery control method and device based on a mobile intelligent express cabinet system. The method comprises the following steps: controlling each express needing to be delivered to be correspondingly loaded into an intelligent express cabinet at each sorting line grid; after the intelligent express cabinets completing the loading task are stored in a designated storage area, a transport capacity request is sent; each unmanned vehicle responding to the transport capacity request is controlled to respectively drive to a corresponding unmanned vehicle boxing waiting area for loading waiting; in response to query requests of corresponding target placement positions of all the intelligent express delivery cabinets on the unmanned vehicles, querying the corresponding target placement positions according to the identification information codes of the intelligent express delivery cabinets, and sending the target placement positions to the corresponding unmanned vehicles; and controlling the unmanned vehicle to plan a driving path of the unmanned vehicle according to each destination placement position, and delivering each intelligent express cabinet to the corresponding destination placement position according to the planned driving path. The method has the advantages of being simple in implementation method, low in cost, high in intelligent degree and equipment utilization rate, high in flexibility and the like.

The invention discloses a project management method, device and equipment and a storage medium, relates to the technical field of cloud, in particular to a management technology of a cloud computing management and control system supporting a multi-architecture processor in a private cloud environment, and is used for reducing project management difficulty and management cost and improving management efficiency when a project is supported to be deployed in a multi-processor architecture environment. The method comprises the steps of obtaining file information associated with a target project; the file information at least comprises a public configuration file and a multi-architecture difference file; wherein the public configuration file is used for storing general configuration information among a plurality of processor architectures; the multi-architecture difference file comprises difference sub-files matched with the processor architectures in the processor architectures respectively, and each difference sub-file is used for storing project deployment information supported by one processor architecture; and based on the public configuration file and the multi-structure difference file, compiling the source code of the target project, and respectively obtaining project deployment files associated with the plurality of processor architectures.

The invention relates to the technical field of air conditioner control optimization, in particular to a control method and device for a multi-connected air conditioning unit, and the control method comprises the steps that an air conditioning area is divided to obtain a plurality of air conditioning sub-areas, and an air conditioning area map is constructed based on the air conditioning sub-areas; and performing video monitoring on the plurality of air conditioning sub-regions based on an infrared camera to obtain infrared videos of the plurality of air conditioning sub-regions, and performing image interception on the infrared videos according to a preset sampling period to obtain an infrared video frame sequence. The air conditioning area is reasonably divided, the whole space is divided into the multiple air conditioning sub-areas, the air conditioning system can be controlled more flexibly, the division can be adjusted according to the actual use condition, and the requirements of different numbers of users can be better met.

The invention relates to a method for improving soil fertility and enzyme activity of a rice field by using a nitrogen-fixing cyanobacteria biological membrane, which comprises the following steps: step 1, expanding propagation of nitrogen-fixing cyanobacteria: selecting anabaena globifera as a rice field application algae species, and performing expanding culture on the algae species to obtain a nitrogen-fixing cyanobacteria secondary algae species; step 2, applying nitrogen-fixing cyanobacteria: applying the nitrogen-fixing cyanobacteria in a rice base fertilizer period and a tillering period, and replacing part of chemical fertilizer with the nitrogen-fixing cyanobacteria to reduce the application amount of the chemical fertilizer; secondly, the nitrogen-fixing cyanobacteria returns to the rice field through biological nitrogen fixation and rotting decomposition of dead algae, the content of nitrogen and carbon in the soil is increased, the soil fertility is improved, and the nitrogen-fixing cyanobacteria can provide nutrient substances for microorganisms in the soil, improve the enzyme activity of the soil and improve the quality of the soil when applied to the rice field.

The invention relates to a garment customization system and method based on the Internet of Things, and belongs to the field of garment customization. The garment customization system based on the Internet of Things comprises a terminal, a size data generation module and a garment customization module. The terminal is used for collecting images and size data uploaded by a user; the size data generation module is used for carrying out feature extraction on the uploaded image and then reconstructing a human body image to generate size data of each part; the clothing customization module is used for matching the image output by the terminal to generate a virtual fitting picture, and the virtual fitting picture is used as a customization effect picture to be sent to the terminal after being subjected to aesthetic evaluation, secondary creation and aesthetic reevaluation; and the terminal combines the customization effect picture with the size data of each part of the human body to generate a garment customization order. According to the invention, based on the virtual fitting technology and the multi-dimensional aesthetic evaluation technology, the highly personalized customization service is provided for the user, and the accuracy of the online customization effect picture and the satisfaction degree of the user are effectively improved.