35results about How to "Realize intelligent optimization" patented technology

The invention provides a vehicle fault online detection and early warning device based on the internet of vehicles and a vehicle fault online detection and early warning method thereof. The device comprises a vehicle-mounted terminal, a remote server side, a vehicle owner mobile phone client side, a maintainer client side and a maintenance manufacturer client side. According to the detection method, the vehicle-mounted terminal acquires vehicle information, wherein the vehicle information includes the data of an OBD interface and the data acquired by a sensor so as to realize vehicle online real-time monitoring; the vehicle information is transmitted to the remote server side to perform big data intelligent analysis so that the existing problems of the vehicle are obtained and early warning is provided and faults can be avoided; besides, a vehicle maintenance scheme can be intelligently provided, and the data are fed back to the vehicle owner and the maintenance shop of the maintainer through the vehicle owner mobile phone client side, the maintainer client side and the maintenance manufacturer client side so that the vehicle owner can understand the situation of the vehicle in real time and take measures for fault prevention, the maintainer can view the data and the analysis result of the remote server side and thus maintenance is facilitated.

The invention discloses a method for identifying parameters of synchronous wind-driven generators on the basis of an improved particle swarm optimization algorithm. The method has the advantages that selection genetic operation, crossover genetic operation and mutation genetic operation are carried out on the basis of the particle swarm optimization algorithm, so that the global search capacity and the local search capacity of the particle swarm algorithm can be improved, and the convergence speed of the particle swarm algorithm can be increased; measured data are directly acquired via a control center, so that the parameters of the synchronous wind-driven generators can be identified in an online manner, an existing method for identifying parameters of wind-driven generators in an offline manner under the condition of machine halt is changed, and normal running of the synchronous wind-driven generators is unaffected; the identified parameters effectively conform to actual running conditions of the synchronous wind-driven generators, and accordingly steady states, dynamic states and transient characteristics of the synchronous wind-driven generators can be effectively reflected.

The invention provides an intelligent precise traditional Chinese medicine skill training assessment system. According to the system, conventional traditional Chinese medicine appropriate skill training methods are combined with advanced informatization techniques, and on the basis of real human body data models, aiming at traditional Chinese medicine appropriate skill training contents such as acupuncture and massage, sense experience of vision, touch sense, auditory sense and the like similar to those of real scenes is provided for users. The system comprises head-worn display and control equipment, an action capturing subsystem, a gravity sensation subsystem, an intelligent simulation human model, a needle type simulation instrument, an equipment access management subsystem, a comprehensive demonstration subsystem, an intelligent traditional Chinese medicine skill assessment subsystem and a data 'cloud' platform. By adopting the platform, the training effect of a user can be effectively improved, the training period of learners can be greatly shortened, the actions of the learners can be recorded and analyzed in real time, action results can be accurately judged, the optimized customization of training contents can be achieved, guidance teaching is achieved in the training process, and training schemes can be intelligently optimized.

The invention provides a method for realizing main steam pressure traction optimization of a steam turbine on the basis of mathematical modeling of heat loss correlated quantity and relates to a control technology of variable working condition optimized operation of a power station steam turbine. According to the method, a correlation variable K between heat loss and main steam pressure of a turbine unit is proposed; according to core parameters correlated with the main steam pressure and heat loss of the turbine unit, such as main steam flow, main steam pressure, exhaust steam pressure of a high-pressure cylinder, exhaust steam temperature of the high-pressure cylinder, attemperating water flow, one-section extraction pressure, one-section extraction temperature, rotation speed of a small steam turbine or current of an electric pump and condenser backpressure, a comprehensive equivalent heat loss K is obtained through an equivalent enthalpy drop method; and an operation tracking optimization model is established by taking the intermediate variable K as a target function. Through the modeling optimization of the intermediate variable K, the main steam pressure curve of the turbine unit under different main steam flows is determined and the tracking control of the main steam pressure is performed further. A characteristic database is updated according to the real-time operation parameters so that the main steam pressure curve is closer to the theoretically optimized operation curve of the turbine unit.

The invention discloses a method for realizing main steam pressure tracking optimization of a steam turbine unit on the basis of performing mathematical modeling on thermal loss associated amount, and relates to a variable working condition optimization operation control technology for the steam turbine unit of a power station. The invention provides an association variable K between thermal loss and main steam pressure of the unit, and an operation tracking optimization model is established by taking the intermediate variable K as an objective function according to a plurality of core parameters of main steam flow rate, main steam pressure, main steam temperature, exhaust steam pressure of a high-pressure cylinder, exhaust steam temperature of the high-pressure cylinder, rotational speed of a small steam machine (or current of an electric pump), back pressure of steam condenser and the like, which are associated with the main steam pressure and the thermal loss. By performing modeling optimization on the intermediate variable K, a main steam pressure curve of the unit under different main steam flow rates can be determined, and the main steam pressure tracking control can be further performed. Weighed updating is performed on a characteristic database according to the related parameters of real-time operation, thereby enabling the main steam pressure curve to be closer and closer to a theoretical optimization operation curve of the unit.

The embodiment of the invention provides a resource configuration method and apparatus, and an electronic device. The method comprises the following steps: obtaining running parameters of each task ina plurality of tasks, calculating a target function of the task according to the running parameters of each task, obtaining a total amount of preset resources of a server cluster, calculating an optimal resource use amount of each task according to the total amount of preset resources and the target function of each task, sending the optimal resource use amount of each task to the server cluster,so that the server cluster can run the corresponding task according to the optimal resource use amount of each task. By adoption of the resource configuration method and apparatus provided by the embodiment of the invention, intelligent optimization of resources manually configured by service personnel is achieved, the resource use of different tasks is effectively coordinated to achieve a globaloptimal effect, the resource utilization rate of the server cluster is effectively improved and the resource waste is reduced.

The invention provides a logistics box distribution method and apparatus, and electronic equipment, and relates to the technical field of logistics management. The logistics box distribution method comprises: obtaining logistics information of to-be-distributed logistics boxes and position information of logistics cabinets, wherein the logistics information comprises delivery addresses; respectively calculating distances between the delivery addresses of the logistics boxes and the position information of the logistics cabinets; selecting the logistics cabinets with the above distances less than a preset threshold as alternative logistics cabinets; respectively obtaining storage states corresponding to the alternative logistics cabinets; and determining a target logistics cabinet according to the storage states. According to the logistics box distribution method and apparatus, and the electronic equipment, factors including the delivery distances and the storage spaces etc. of the logistics cabinets are comprehensively considered, intelligent optimization of the distribution of the logistics boxes is realized, the storage space is effectively utilized, the delivery time is reduced, and the delivery efficiency is improved.

The invention discloses an unmanned aerial vehicle multi-tower inspection optimization method and terminal under limited inspection time, and belongs to the field of unmanned aerial vehicle inspection. The method comprises the following steps: generating a map of an inspection area in advance, and marking towers in the inspection area in the map; receiving an inspection task for a specified numberof towers in the inspection area, and determining a starting point and an ending point of inspection; acquiring endurance time of the unmanned aerial vehicle; calculating an inspection sequence of the towers and a flight path of the unmanned aerial vehicle by adopting a preset algorithm according to the inspection task, the endurance time of the unmanned aerial vehicle and the position information of the designated number of towers, the starting point and the terminal point to obtain an inspection scheme; and issuing a driving instruction to drive the unmanned aerial vehicle to execute an inspection task according to the inspection scheme. The terminal comprises a setting module, a confirmation module, an acquisition module, an optimization module and a driving module. According to the invention, the intelligent optimization of an unmanned aerial vehicle multi-tower inspection scheme under limited inspection time is realized, it is ensured that the unmanned aerial vehicle completes aninspection task more effectively and intelligently, and the efficiency is improved.

The invention relates to a structure optimization method for a low frequency electromagnetic sensor based on a genetic algorithm. The method is suitable for the structure design of a COMSOL analog low frequency electromagnetic sensor model and the shape reconstruction for defect detecting and belongs to the field of nondestructive detection. The method comprises the following steps: on the basis of simplifying the COMSOL analog low frequency electromagnetic sensor model, parameterizing an optimization model of the COMSOL analog low frequency electromagnetic sensor and defining the reading paths for different variables; setting a genetic optimized fitness function and main parameters including an algorithm running parameter and a control parameter; compiling a dynamic link function, calling for the COMSOL model by MATLAB and constructing a channel for mutually transferring data; calling a COMSOL genetic algorithm for optimizing the parameters of the low frequency electromagnetic sensor model, and while acquiring the fitness function meeting the convergence criterion, acquiring an optimized result, namely, the optimized structure parameter of the low frequency electromagnetic sensor. According to the method provided by the invention, the limitation of the COMSOL single assignment operation is broken through and the intelligent optimization of the COMSOL model parameters is realized.

The invention discloses an internet-of-things and cloud computing based intelligent monitoring and fault diagnosis system for mine ventilators. An operating process of the system includes the steps of 1, establishing a ventilator monitoring and fault diagnosis system for each ventilator; 2, integrating all ventilator monitoring and fault diagnosis systems in a mine and a ventilation safety monitoring system to establish mine ventilator air network monitoring systems, through an internet-of-things technology; 3, integrating the mine ventilator air network monitoring systems to establish a group-level ventilator air network monitoring system, through the internet-of-things technology; 4, integrating ventilator users, ventilator manufacturers and ventilator air network fault diagnosis experts in a work environment through a cloud computing platform, improving functions of the ventilator monitoring and fault diagnosis systems to multi-ventilator intelligent control so as to achieve air network intelligent optimization and ventilator fault auxiliary diagnosis. The system has the advantages that a ventilation system is more efficient and reliable, safety production of the mine is guaranteed, an air network is efficient and stable, energy is saved, and consumption is reduced.

The invention provides an ultra-fast pulse laser-cold spraying surface processing method for a thin-wall structure. The method is mainly used for solving the surface defect problem of a metal thin-wall structure so as to achieve the rapid and high-quality repair. According to the technical scheme, the method comprises the following steps that firstly, a thin-wall structure defect surface model isconstructed based on a three-dimensional measurement reverse reconstruction technology; a process parameter database is built by combining with an artificial intelligence technology; the trajectory ofeach movement part is reasonably planned through a robot technology; the powder particle flow state is restrained through a powder charged device; and an ultra-short pulse laser technology is introduced into a cold spraying repair technology, and rapid repair on the surface of a metal thin-wall component is achieved. By applying the processing method, the problems of deformation and reduction onperformance of the aluminum alloy thin-wall structure caused by high heat input in a conventional laser cold spraying process can be solved, and meanwhile, the rapid surface repair with high process stability and high quality reliability can be realized.

The invention discloses a wireless radio frequency communication-based water underfloor heating system. The wireless radio frequency communication-based water underfloor heating system comprises a central control box, a water collecting and dividing unit, electrothermal actuators, a temperature detector, a temperature controller and actuating elements, wherein the water collecting and dividing unit is connected with the actuating elements through the electrothermal actuators; a processor I and a wireless radio frequency transmitting device are arranged inside the temperature controller; the temperature detector is connected with the processor I; the processor I is connected with the wireless radio frequency transmitting device; a wireless radio frequency receiving device, a processor II and control terminals are arranged inside the central control box; the wireless radio frequency transmitting device is in wireless radio frequency communication with the wireless radio frequency receiving device; the wireless radio frequency receiving device is connected with the processor II; the processor II is connected with the control terminals; the control terminals are connected with the electrothermal actuators. The temperature controller is in wireless radio frequency communication with the central control box, so that the wireless radio frequency communication-based water underfloor heating system is easy to mount and convenient to maintain, and thus the laying cost and the later maintenance cost of the water underfloor heating system are greatly reduced.

The invention discloses a subway departure scheduling method and system, and the method comprises the following steps: obtaining passenger riding information, line information and regular train information, and building a subway environment state matrix; obtaining metro reward and punishment data, and establishing a departure decision output by metro reward and punishment for judging a departure effect and generating a new departure decision; predicting a new environment state matrix at the next time point according to the subway environment state matrix and the riding information, and updating a departure decision output by the subway reward and punishment; inputting the subway environment state matrix and the reward and punishment data at each time point into a convolutional neural network for training, outputting a train departure decision after training, and executing subway departure according to the train departure decision. According to the method and the system, a Policy gradient algorithm is adopted to carry out reward and punishment output according to a subway environment state, intelligent optimization of subway scheduling can be realized, and an output result of output subway scheduling can more accord with a humanized design in combination with a convolutional neural network.

The invention discloses an interchange channel layout method and system for automatically changing and moving an existing road along a railway, a terminal and a readable storage medium. The method comprises the following steps: S1, constructing an optimization model of a road and a railway interchange channel line; S2, performing unit grid division on the research area, and decomposing path search into two non-cross section search and cross section search; S3, performing path search on the two non-crossed sections and the crossed section based on the optimization model; and S4, splicing and integrating the N paths, the M paths and the P cross section local lines in the step S3 to form a plurality of complete lines, determining an optimal line by taking an optimization function as a target function, and performing curve fitting of a plane and a longitudinal section based on the optimal line to obtain a final line scheme. The method is decomposed into path search of non-crossing sections and crossing sections, coupling interaction of connecting points and crossing points is weakened, and road and railway interchange channel optimization is achieved.

The invention discloses an internet-of-things and cloud computing based intelligent monitoring and fault diagnosis system for mine ventilators. An operating process of the system includes the steps of 1, establishing a ventilator monitoring and fault diagnosis system for each ventilator; 2, integrating all ventilator monitoring and fault diagnosis systems in a mine and a ventilation safety monitoring system to establish mine ventilator air network monitoring systems, through an internet-of-things technology; 3, integrating the mine ventilator air network monitoring systems to establish a group-level ventilator air network monitoring system, through the internet-of-things technology; 4, integrating ventilator users, ventilator manufacturers and ventilator air network fault diagnosis experts in a work environment through a cloud computing platform, improving functions of the ventilator monitoring and fault diagnosis systems to multi-ventilator intelligent control so as to achieve air network intelligent optimization and ventilator fault auxiliary diagnosis. The system has the advantages that a ventilation system is more efficient and reliable, safety production of the mine is guaranteed, an air network is efficient and stable, energy is saved, and consumption is reduced.

The present invention discloses a live plant body coding artistic picture production system and method. The system comprises unit live plant body color lumps, a live plant body color palette module, a frame module, a drawing robot and a management system. The unit live plant body color lumps are standard-size single-color plants arranged in the live plant body color palette module; A plurality of spaces with standard sizes capable of holding unit live plant body color lumps are arranged at the live plant body color palette module and the frame module in the uniform array arrangement mode; and the drawing robot has a vision sensor which is in communication connection with the management system and is configured to receive an instruction of the management system select the unit live plant body color lumps with colors according with the requirements from the live plant body color palette module and take out and accurately put the unit live plant body color lumps to an assigned position in the frame module. The single-color plants are subjected to standardization and are taken as the minimum unit pixels of the artistic picture to drive the drawing robot to employ the color palette module to complete the live plant body copy of the artistic picture so as to realize combination of the painting art and industrialization greening product production technology.

The invention discloses a white list optimization method, which comprises the steps of determining whether a white list interface matched with a to-be-detected interface exists in a preset white listor not if the to-be-detected interface is detected; if the to-be-detected interface exists, determining a to-be-detected page corresponding to the to-be-detected interface and a white list page corresponding to the white list interface, and calculating the similarity between the to-be-detected page and the white list page; and if the similarity is smaller than a preset threshold, deleting the white list interface from the white list, and performing vulnerability detection on the to-be-detected interface. The invention further discloses a white list optimization device and equipment and a computer readable storage medium. According to the method, whether the to-be-detected interface is in the white list or not is judged, the to-be-detected page of the to-be-detected interface is detected, whether the to-be-detected interface needs to be optimized or not is judged according to the similarity between the to-be-detected page and the white list page recorded in the white list, the white list is accurately optimized, and intelligent optimization of the white list is achieved.

The invention relates to a parameter identification method of an asynchronous motor based on an improved particle swarm optimization algorithm. Based on a standard particle swarm optimization algorithm, the maximum weighting coefficient (as the following formula) and the minimum weighting coefficient (as the following formula) are set in batches respectively; a random mutation operator is added, and the strategy of adding the mutation operator to perform random mutation on gbest improves the ability of the algorithm to jump out of local convergence, improves the problem of premature falling into local optimum of the particle swarm, expands the search scope of particles, improves the global searching ability and convergence speed of the particle swarm optimization algorithm, reduces the risk of falling into the local optimum, and takes both precision and efficiency of an optimization process into account. According to the parameter identification method of the asynchronous motor based on the improved particle swarm optimization algorithm provided by the invention, the measuring value of each working characteristic of the asynchronous motor is obtained by measuring, the improved particle swarm optimization algorithm is used to realize the static parameter identification of the asynchronous motor, and the method still has higher identification accuracy in the presence of noise.

The invention provides an air source heat pump hot-air blower. The air source heat pump hot-air blower comprises an indoor unit and a movable detecting controller, wherein the indoor unit comprises apurifying module, a common module and a humidifying module; the movable detecting controller comprises a detecting module and a control module; and the control module can control the indoor unit to enter a purifying module, a humidity regulating mode or a common regulating mode according to detecting information of the detecting module so as to control the purifying module, the common module and the humidifying module. The air source heat pump hot-air blower is reasonable in structure, can effectively improve a function of the air source heat pump hot-air blower, and monitors indoor environment quality in real time. Furthermore, the air source heat pump hot-air blower also can realize intelligent optimization on an indoor unit device of a low-environment-temperature air source heat pump hot-air blower, can intelligently supply heat in a clean mode, further can intelligently improve quality of indoor air, and reduces capacity of winter building heating and purifying equipment, so that building energy consumption is reduced.

The invention provides an intelligent method for optimizing working procedure of a semiconductor packaging production line, applying particle swarm optimization (PSO) to optimize the working procedure in a semiconductor packaging process, modeling and finding the solution, taking processing center as a unit, building a mapping relation between problem to be solved and particle swarm, using particles to express optional solutions to the problem, and finding the optimized solution under the guidance of corresponding target; each particle swarm optimization subproblem is using processing time of the machine on the production line for different products to encode the particles to determine particle swarm optimization space and making time sequence decoupling on the optimization problem to be solved, obtaining the corresponding subproblem and then dividing the problem space and determining a mapping relation between the divided space and each subproblem to find particle swarm optimization solution of each subproblem, thus obtaining an optimized machine processing time allocating solution and machine occupation ratio. The practice indicates that PSO has the advantages simple concept, convenient implementation, rapid convergence, etc.

The invention provides an omnibearing electric power economic business index analysis system and method, and relates to the research field of the relationship between the electric power economic business index and economic growth. The system comprises a first input module, a second input module, an index prediction module and an output module. A cross-discipline method is applied, on the basis of cross-correlation analysis in statistics, mature methods in the fields of economy, finance, industry, foreign trade and the like are combined, prosperity analysis is completely introduced into the power industry, and a novel statistical power economy prosperity index is extracted through multi-dimensional power utilization data mining. The operation condition and development situation of provincial macroeconomy are objectively reflected, the important function of watching economy through electric power is achieved, and a quantitative index is provided for the economic operation trend.

The invention discloses an omnibearing electric power economic prosperity index analysis system and an analysis method thereof, and relates to the field of research on a relationship between the electric power economic prosperity index and economic growth. The system comprises an index construction module, an index prediction module, an index compiling module and a signal compiling module. The analysis method comprises the following steps: firstly, selecting an index for constructing a consistency index; then predicting the index, taking a predicted value as a leading index and taking an actual value as a consistency index; finally, compiling a signal lamp system. By adopting the interdisciplinary method, taking cross-correlation analysis in statistics as a basis, and combining mature methods in the fields of economy, finance, industry, foreign trade and the like, prosperity analysis is completely introduced into the power industry, a novel statistical power economy prosperity index ismined and extracted through multi-dimensional power utilization data, provincial macroeconomic operation conditions and development situations are objectively reflected, an important function of 'looking at economy through power' is realized, and quantitative indexes are provided for the economic operation trend.

Embodiments of the present invention provide a resource configuration method, device, and electronic equipment, wherein the method includes: acquiring the operating parameters of each of the multiple tasks, and calculating the objective function of the task according to the operating parameters of each task, Obtain the total amount of preset resources of the server cluster, and calculate the optimal resource usage of each task according to the preset total amount of resources and the objective function of each task, and send the optimal resource usage of each task to the server Cluster, so that the server cluster can run corresponding tasks according to the optimal resource usage of each task. The embodiment of the present invention realizes intelligent optimization of resources manually configured by business personnel, effectively coordinates resource usage of different tasks, achieves global optimal effect, effectively improves server cluster resource utilization, and reduces resource waste.

The invention relates to the technical field of big data, and discloses a structured data tool optimization method, which comprises the steps of: acquiring an original structured data tool, and establishing a data synchronization mechanism for the original structured data tool and a pre-constructed source database to obtain an initial structured data tool; adding a link copy copying function intoa data transmission link of the initial structured data tool to obtain a standard structured data tool; establishing a synchronous updating mechanism for a configuration table in the standard structured data tool and a corresponding data table in the source database to obtain a target structured data tool; and performing search optimization on a configuration table in the target structured data tool by utilizing a preset search optimization algorithm to obtain an optimized structured data tool. The invention further provides a structured data tool optimization device, electronic equipment anda computer readable storage medium. According to the structured data tool optimization method and the structured data tool optimization device, intelligent optimization of the structured data tool canbe realized.

The invention discloses an overpass layout method, system, terminal and readable storage medium for automatically changing and moving existing roads along a railway line. The method includes: step S1: constructing an optimization model of road and railway overpass lines; step S2: Carry out cell grid division in the research area, and decompose the path search into two non-intersecting segment searches and intersecting segment searches; Step S3: perform path search on two non-intersecting segments and intersecting segments based on the optimization model; Step S4: use step The N paths, M paths and P intersecting partial lines in S3 are spliced ​​and integrated to form several complete lines, and the optimal line is determined with the optimization function as the objective function, and the curves of the plane and longitudinal sections are carried out based on the optimal line Fitting to get the final route scheme. The invention decomposes into path search of non-intersection section and intersection section, weakens the coupling interaction between connection point and intersection point, and realizes the optimization of highway and railway overpass.

The invention discloses an aircraft assembly measurement field layout method based on a genetic algorithm, comprising the following steps: establishing an assembly measurement field layout model based on 0-1 planning; solving the assembly measurement field layout model through a genetic algorithm to obtain an optimized layout of the measurement field. The present invention realizes the intelligent optimization of the measurement field layout by establishing a measurement field layout optimization model based on 0-1 planning, and then using a genetic algorithm to solve it, and lays a foundation for high-precision measurement orientation points. The layout optimization model of the measurement field is established by using 0-1 planning, so that the layout problem of the complex measurement field becomes clear, concise and easy to solve; and then the genetic algorithm is used to solve the model, which is efficient and convenient.

The invention discloses a blockchain service safety protection strategy management and control system and method. The blockchain service safety protection strategy management and control system comprises a server deployed in a server and clients deployed in blockchain service nodes, and the server is used for defining a blockchain service safety protection strategy and distributing the defined blockchain service safety protection strategy to the clients; the client is used for performing safety protection on each blockchain node according to the blockchain service safety protection strategy and returning an execution condition of the blockchain service safety protection strategy to the server; and the server further analyzes the execution condition of the blockchain service safety protection strategy returned by the client, and optimizes and upgrades the blockchain service safety protection strategy according to an analysis result. By adopting the technical scheme, a unified, dynamic and personalized safety protection strategy can be provided for various nodes of a large blockchain system.

The invention discloses an aircraft assembly measurement field layout method based on a genetic algorithm. The method comprises the following steps: establishing an assembly measurement field layout model based on 0-1 planning; and solving the assembly measurement field layout model through a genetic algorithm to obtain a measurement field optimized layout. The measurement field layout optimization model based on 0-1 planning is established, and then the genetic algorithm is used for solving, so that intelligent optimization of the measurement field layout is realized, and a foundation is laidfor high-precision measurement of orientation points. A measurement field layout optimization model is established by utilizing 0-1 planning, so that a layout problem of a complex measurement field becomes clear and concise in expression and is convenient to solve; and the genetic algorithm is used to solve the model, which is efficient and convenient.

The invention relates to a structure optimization method for a low frequency electromagnetic sensor based on a genetic algorithm. The method is suitable for the structure design of a COMSOL analog low frequency electromagnetic sensor model and the shape reconstruction for defect detecting and belongs to the field of nondestructive detection. The method comprises the following steps: on the basis of simplifying the COMSOL analog low frequency electromagnetic sensor model, parameterizing an optimization model of the COMSOL analog low frequency electromagnetic sensor and defining the reading paths for different variables; setting a genetic optimized fitness function and main parameters including an algorithm running parameter and a control parameter; compiling a dynamic link function, calling for the COMSOL model by MATLAB and constructing a channel for mutually transferring data; calling a COMSOL genetic algorithm for optimizing the parameters of the low frequency electromagnetic sensor model, and while acquiring the fitness function meeting the convergence criterion, acquiring an optimized result, namely, the optimized structure parameter of the low frequency electromagnetic sensor. According to the method provided by the invention, the limitation of the COMSOL single assignment operation is broken through and the intelligent optimization of the COMSOL model parameters is realized.