103results about How to "Guaranteed pertinence" patented technology

The invention relates to the technical field of mixed learning, in particular to an online and offline combined digital interactive teaching method and system, and the method comprises the following steps: collecting online and offline learning data of students, carrying out the statistics of the number and frequency of various interaction types, including the number of discussion times, the number of question answering times and the group cooperation frequency, and generating an initialized interactive data set. According to the method, redundancy and deficiency of various interactions are calculated through the information entropy technology, information vacancy in learning is helped to be recognized, teaching content is optimized, student requirements are matched, the optimized design defines a learning target, an expected interaction frequency is set, the interaction adjustment effect is verified through a simulation test, it is ensured that teaching activities are more targeted, and the teaching efficiency is improved. The interaction frequency is dynamically adjusted in real-time teaching, the sense of participation of students is improved, the learning effect can be monitored in real time, the learning motivation and achievement of the students are improved, and implementation of personalized learning is promoted.

The invention belongs to the technical field of machine control and management, and particularly discloses a household unmanned control and management system based on a washing robot, which comprises a washing robot main body and a washing control system, the washing control system comprises a clothes identification and analysis module, an environment information acquisition module, a clothes cleaning confirmation module, a user interaction verification terminal, a database and a clothes processing execution module. According to the invention, when the clothes information of the dirty clothes placement area is collected, whether the dirty clothes placement area needs layered detection is judged according to the collected overall scanning visual image, overall spectral data and overall scanning depth image, so that the problem of insufficient attention to clothes identification accuracy at present is effectively solved; according to the method, the mode, the water amount and the adding amount of the detergent of subsequent automatic clothes washing can be accurately controlled, misjudgment is reduced, and meanwhile, the flexibility and pertinence of washing setting are guaranteed by confirming the washing operation instruction.

The invention discloses a micro course generation method based on OCR recognition and a server, and relates to the field of image data processing, and the method comprises the steps: collecting maintenance record document image data, and carrying out the optical character recognition processing of the maintenance record document image data, and obtaining digital text data; performing natural language processing on the digital text data according to a preset bidirectional encoder representation model, and integrating the terminology information, the fault code information and the operation step information into structured knowledge data; obtaining a knowledge level parameter and a post information parameter of the target user, and performing difficulty grading on the structured knowledge data according to the knowledge level parameter to obtain difficulty grading knowledge data; performing knowledge range screening in the difficulty grading knowledge data according to the post information parameters to obtain target knowledge data; and selecting teaching materials matched with the target knowledge data from the knowledge resource library, and generating a micro course resource bundle according to the teaching materials. By implementing the method, the updating efficiency of the training data can be improved.

The invention belongs to the technical field of multi-scene patrol analysis management, and particularly discloses a multi-scene intelligent shooting patrol analysis management system for regional security and fire protection. Comprising a regional information recording module, a regional security monitoring module, a regional security analysis module, a regional hidden danger monitoring module, a regional hidden danger analysis module, a regional fire-fighting monitoring module, a regional fire-fighting analysis module, a regional early warning confirmation module and a regional early warning management terminal. According to the invention, the pertinence of regional monitoring analysis is guaranteed by analyzing the security and protection qualified index, the fire hazard qualified index and the fire hazard qualified index of each monitoring region, so that the discovery timeliness of potential problems is improved, and meanwhile, according to the security and protection qualified index, the fire hazard qualified index and the fire hazard qualified index of each monitoring region, the monitoring accuracy is improved. And the early warning item of each monitoring area is confirmed, so that the accuracy and effectiveness of early warning are guaranteed, and the management efficiency of area management is improved.

The invention discloses an oil sunflower field precise fertilization control system based on an unmanned aerial vehicle hyperspectral technology, and relates to the technical field of fertilization control. The system carries out precise region division on an oil sunflower field by utilizing a GIS technology through fusion of multi-source data such as hyperspectral data, soil humidity and temperature; and accurate fertilization can be carried out in different management areas according to soil characteristics and crop requirements. The differentiated fertilization strategy can reduce excessive fertilization and fertilizer waste and optimize the utilization efficiency of the fertilizer. The crop growth model is established through the deep learning technology, and the system can accurately calculate the required fertilization amount according to the specific growth conditions and historical data of each region, so that the growth conditions of the oil sunflowers are optimized, and the overall yield of crops is improved. The problem that a traditional fertilization system is difficult to effectively deal with soil and environment differences in different areas is solved. Through a hyperspectral technology and multi-source data acquired by a sensor, the system can realize accurate fertilization according to environmental differences in a field.

The invention relates to the technical field of data processing, in particular to a construction method and system for a neural rehabilitation evaluation model. The method comprises the following steps: acquiring multi-modal data of a neurological rehabilitation patient; performing feature extraction according to the multi-modal data of the neurological rehabilitation patient to obtain multi-modal feature data of the neurological rehabilitation patient; performing data classification on the multi-modal feature data of the neurological rehabilitation patient to obtain multi-modal feature classification data; and marking the multi-modal feature data of the neurological rehabilitation patient by using the multi-modal feature classification data to obtain multi-modal feature marking data of the neurological rehabilitation patient so as to carry out neurological rehabilitation evaluation model construction auxiliary work. According to the method, the model capable of comprehensively and objectively evaluating the rehabilitation progress of the neurological rehabilitation patient is constructed in an auxiliary manner, so that a scientific basis is provided for rehabilitation treatment.

The invention relates to the technical field of separation devices, and discloses a cyclone separator optimization system and method based on machine learning, and the system comprises a user operation module, a numerical simulation module and a deep learning module. The method comprises the steps that when a user terminal inputs cyclone separator parameters in a cloud platform, a system calls a cyclone separator parameter database; if no corresponding cyclone separator parameter exists in the cyclone separator parameter database, performing analogue simulation calculation according to the cyclone separator parameter input by a user, and establishing a flow prediction model according to a simulation result; the flow prediction model performs prediction according to the simulation result; after the prediction is finished, performing comparison according to a prediction result; and finally obtaining optimized parameters required by the parameters of the cyclone separator, and transmitting the optimized parameters to a user terminal through the cloud platform. According to the method, the separation efficiency of cyclone separators with different designs is predicted, and manpower, material resources, time, cost and the like are saved in actual production.

The invention relates to a method for modeling a photovoltaic power station for relay protection by using fault recording data. The method comprises the following steps: step 1, acquiring a fault recording file by a fault recording analysis system; 2, processing voltage and current data based on the fault recording file obtained in the step 1, and then calculating the short-circuit current of the photovoltaic power station; 3, obtaining a latest short circuit calculation model based on the voltage and current data processed in the step 2, and obtaining a final short circuit calculation model through multiple times of model correction; and 4, performing short-circuit calculation by using the short-circuit calculation model corrected in the step 3. According to the invention, simulation and actual short-circuit tests can be avoided.

The invention relates to the technical field of physiological signal processing, and discloses a motion sickness detection device and system and a storage medium. Based on a signal preprocessing module, a feature extraction module, a feature weighting module, a global feature capture module and a classification detection module which are sequentially connected, the device executes the following steps: performing preprocessing and data enhancement on an electroencephalogram signal to obtain a preprocessed electroencephalogram signal; a convolution module is used for sampling up and down in a time frequency dimension to obtain local time frequency characteristics of the preprocessed electroencephalogram signals; performing feature weighting on the local time-frequency features to obtain a feature weighted graph; inputting the feature weighted graph into a Transform module to capture global features to obtain the global features; according to the method, global features are used as data to be classified to be input into a full connection layer and finally pass through a Softmax layer to calculate prediction probabilities of multiple categories, so that efficient feature extraction and accurate classification of the electroencephalogram signals are realized, and motion sickness symptoms of a subject are effectively monitored and evaluated.

The invention discloses an off-road training plan generation method and device, electronic equipment and a computer storage medium. The method comprises the steps of obtaining feature information of a target off-road race and an initial long-term training load value of a user; according to the feature information and the initial long-term training load value, judging whether the user can successfully complete the target off-road race or not; and when it is judged that the user can successfully complete the target off-road running event, determining course arrangement of an off-road running training plan based on the training course library. In the whole off-road running training plan generation process, the off-road running training plan with pertinence, reasonability and scientificity can be generated, and therefore the off-road running ability of the runner can be improved in a targeted mode by combining the characteristics of the target off-road running event and the actual ability of the runner.

The invention provides a short-circuit reverse-sequence protection method for three-phase alternating current and related equipment, and relates to the technical field of new fields. Complex three-phase current information is converted into positive, negative and zero-sequence components which are easier to analyze through symmetric component decomposition. By calculating the anti-sequence component ratio and the zero-sequence component ratio, the ratios are kept relatively stable during normal load change, so that the influence of load change on fault judgment can be effectively eliminated. By introducing a first-order derivative and a second-order derivative, not only can the instantaneous characteristic change when the fault occurs be reflected, but also the dynamic process of fault development can be reflected, which is essentially different from a method which purely depends on a fixed threshold. According to the multi-dimensional feature analysis method, load fluctuation, harmonic interference and real faults can be effectively distinguished, the accuracy of fault recognition is improved, and misoperation of a protection device is avoided.

The invention provides a structural design optimization method, device and equipment for a cylindrical heat absorption tower, and relates to the technical field of data processing. The method comprises the following steps: determining optimization variables and constraint conditions of structural characteristics of the heat absorption tower according to structural design requirements of the cylindrical heat absorption tower; according to a genetic algorithm, initial population individuals are randomly generated within the limitation range of the optimization variables, constraint condition verification is carried out on the optimization variables corresponding to the initial population individuals, and qualified individuals are screened out; based on a crossover and variation rule, optimization variables corresponding to the qualified individuals are adjusted, and new individuals are generated through parameter recombination and random variation; and calculating a fitness value of a new individual according to an optimization objective function of the heat absorption tower, dynamically adjusting control parameters of a crossover and variation rule, and repeatedly iteratively optimizing a population until optimization variables are converged to an optimal solution meeting design requirements. According to the technical scheme, the efficiency and comprehensiveness of structural design optimization of the cylindrical heat absorption tower can be improved.

The invention discloses a platform operation and maintenance method, electronic equipment, a medium and a product, and relates to the technical field of artificial intelligence, and the method comprises the steps: obtaining the current state information of a service platform; a current state feature vector is extracted from the current state information through a preset bert pre-training model, and the preset bert pre-training model is obtained through fine adjustment of a preset fine adjustment operation and maintenance task; and inputting the current state feature vector into a preset neural network decision model to obtain a target operation and maintenance strategy of the service platform. According to the method, automation and intelligentization of operation decision making are realized, and the decision making network model can automatically learn and optimize from a large amount of network data, so that the accuracy and effect of the operation and maintenance strategy are continuously improved, the manual intervention demand and dependence are reduced, the operation efficiency is improved, and the labor cost is reduced.

The invention discloses a business data processing method and system based on multiple channels, and the method comprises the steps: obtaining the basic information of a to-be-sold commodity and a preset advertisement putting amount, calculating the average re-purchase period of the commodity through analyzing the historical business data of each channel, comparing the remaining re-purchase time of a user with the average re-purchase period, and determining a first intention user. If the number of the first intention users meets the advertisement putting demand, allocating the advertisement putting amount and screening the advertisement putting users based on the remaining re-purchase time and a preset advertisement putting preference prediction algorithm; otherwise, the second intention users who have purchased the commodities recently are found out by analyzing the commodity set with high relevance, and the final advertisement putting object is determined by combining the conditions of the two types of intention users. According to the invention, by analyzing the multi-channel business data and the user re-purchase cycle, the intentional user is accurately positioned, the advertisement putting is optimized, and the advertisement conversion rate and the resource utilization rate are effectively improved.

The invention provides an obstacle association method and device, computer equipment and a storage medium, and the method comprises the steps: obtaining measurement data from at least one sensor, and enabling the measurement data to comprise a plurality of obstacle measurements and detection information thereof; for each obstacle measurement to be associated, selecting a target reference point type from a plurality of predefined candidate reference point types according to detection information of the obstacle measurement to be associated; determining a measurement reference point from the detection information of the obstacle measurement based on a target reference point type selected for each obstacle measurement; determining a matching measure between a measurement reference point and a track reference point based on the measurement reference point measured by the obstacle and the track reference point determined for the fused track; according to the calculation result of the matching measurement between all the obstacle measurements and all the fused tracks, the association relationship between the obstacle measurements and the fused tracks is determined, and the accuracy and the reliability of obstacle association can be remarkably improved by adopting the method.

The invention provides an urban green infrastructure comprehensive benefit applicability evaluation method based on subjective and objective weights. The urban green infrastructure comprehensive benefit applicability evaluation method comprises the steps of establishing a basic evaluation system, screening indexes, calculating index weights, calculating quantitative indexes, calculating qualitative indexes, performing grading evaluation, performing standardized score assignment and performing comprehensive evaluation. The basic evaluation system is of a three-layer structure and covers four criteria of runoff regulation and storage benefits, environmental benefits, economic benefits and social benefits and 19 indexes; a subjective weight is determined through an analytic hierarchy process, an objective weight is determined through an entropy weight method, and a comprehensive weight is obtained in combination with a D-S evidence theory fusion method; quantitative indexes are calculated through methods such as hydrological simulation, and qualitative indexes are rated by public; the indexes are unified into dimensionless scores through standardized score assignment, and finally an evaluation result is obtained through weighted summation. According to the method, the applicability quantitative evaluation of matching of the typical green infrastructure and the site condition construction target is realized, and a scientific and quantitative decision support tool is provided for sponge city planning.

The application relates to a matching welding method and system of an automobile bumper, and relates to the technical field of welding, which comprises the following steps: collecting first vibration detection information of a bumper beam clamp, second vibration detection information of an energy absorption box clamp and welding parameters of a welding device; determining first vibration offset parameters according to the first vibration detection information; determining second vibration offset parameters according to the second vibration detection information; analyzing the first vibration offset parameters and the second vibration offset parameters to determine the relative offset amount of the energy absorption box; based on the welding parameters, calling a welding current position point and a current welding power; combining the welding current position point and the relative offset amount to determine welding offset influence parameters; when and only when the welding offset influence parameters meet a preset moving reference reference value, combining the welding offset influence parameters and the current welding power to determine welding adjustment information, and outputting the welding adjustment information. The application has the effect of improving the welding quality of the energy absorption box and the bumper beam.

This invention relates to the field of ultra-high performance concrete (UHVPC) curing technology, and more particularly to an intelligent temperature-controlled curing method for UHVPC. The method includes the following steps: generating preliminary temperature-controlled curing data for concrete based on UHVPC mix proportion parameters and temperature-controlled curing requirements data; analyzing the distributed temperature field characteristics of the pouring nodes using UHVPC pouring node data to generate distributed temperature field characteristic data for the pouring nodes; analyzing the temperature evolution and hydration state of the pouring node temperature field based on the distributed temperature field characteristic data and the preliminary temperature-controlled curing data to generate temperature evolution and hydration regulation state data; and performing dynamic temperature-controlled curing analysis on the preliminary temperature-controlled curing data to generate dynamic temperature-controlled curing data for the concrete. This invention achieves intelligent temperature-controlled curing by combining the application of UHVPC.

The application discloses a transfer trip planning method, which is applied to an artificial intelligence service program based on a large language model deployed on a travel service platform and comprises the following steps: obtaining travel demand information input by a user and performing intention recognition to determine the travel intention of the user; determining a target reasoning mode from multiple reasoning modes based on the travel intention; if the target reasoning mode is a first reasoning mode, taking the arrival time of a sub-trip meeting the travel intention as a starting point, reasoning a next sub-trip in a forward direction along a time axis, and sequentially reasoning until at least one transfer trip is planned; and if the target reasoning mode is a second reasoning mode, taking the departure time of a sub-trip meeting the travel intention as a starting point, reasoning a previous sub-trip in a reverse direction along the time axis, and sequentially reasoning until at least one transfer trip is planned. The application can adaptively select a forward or reverse reasoning mode according to the user intention, and simultaneously meet the travel demand of the user for "the earliest arrival" and "the latest departure".

The application provides a vehicle operation data collection method and system, computer equipment and medium, and belongs to the field of vehicle data processing. The method comprises the following steps: obtaining vehicle model information and user demand of a vehicle to be collected; determining data analysis service project content options based on a data analysis service project content information table and vehicle model information corresponding information table, and screening data analysis service project content according to the user demand of the vehicle to be collected; generating a natural language text for the data analysis service project content to obtain a vehicle data collection strategy; collecting environmental data and judging based on data collection conditions; when the environmental data falls within the range of the data collection conditions, collecting operation data of the vehicle to be collected according to the data collection project, and obtaining operation data of the vehicle to be collected. The method can dynamically collect data based on the actual operation state, driving environment and user demand of the vehicle, and ensure the effectiveness of operation data collection.

The application provides an AI-based eye health management and lens fitting recommendation method and system, which captures eye state information through a collection device, synchronously acquires optometry data and eye detection data and pre-processes; inputs the data into an AI analysis model, identifies eye features and analyzes eye health conditions, and generates a health assessment report; based on the report, matches correction and protection schemes and screens adaptive contact lenses in combination with eye use requirements; through the linkage of intelligent wearable devices and special function contact lenses, eye data is monitored and health management suggestions are generated, visual expansion effect is realized, and the evaluation results and recommended schemes are continuously iterated and optimized, realizing the individualization and intelligentization of eye health management and lens fitting recommendation.

The invention provides a washing machine. The washing machine comprises an outer barrel, a first washing mechanism and a second washing mechanism; the first washing mechanism comprises a first inner barrel and a first washing piece, and the second washing mechanism comprises a second inner barrel and a second washing piece; the first washing piece and the second washing piece are movably arranged in the first inner cylinder and the second inner cylinder respectively; the first inner cylinder and the second inner cylinder are not communicated with each other and are communicated with the outer cylinder; when the first washing mechanism and the second washing mechanism are in the independent washing state, the first inner drum and the second inner drum are static, and the first washing piece and the second washing piece move independently to wash clothes in the first inner drum and the second inner drum respectively; when the first washing mechanism and the second washing mechanism are in a synchronous dewatering and drainage state, the first washing piece and the second washing piece are static, the first inner cylinder and the second inner cylinder rotate synchronously, and water in the first inner cylinder and the second inner cylinder is discharged into the outer cylinder and is discharged through a drainage port of the outer cylinder; healthy partitioned washing is achieved, and the cleaning effect of small clothes is remarkably improved.

The invention relates to the technical field of microphone welding quality detection. The microphone welding direction detection method comprises the steps that acoustic feedback information of a microphone to be detected is obtained, the acoustic feedback information is processed, high-frequency interference and background noise are removed, filtered information is obtained, and the microphone welding direction is detected. Extracting frequency spectrum feature information in a preset frequency range from the filtered information, generating target frequency band information, performing phase calculation on the target frequency band information to obtain actual phase value information, inputting the actual phase value information into a welding direction judgment model, generating a feature difference value, and judging the welding direction based on the feature difference value. And determining the microphone with the wrong welding direction. The welding direction detection device has the effect of improving the reliability of welding direction detection.

The present invention provides an urban road collapse disaster risk assessment method and system based on artificial intelligence, comprising: step S1, obtaining collapse-related data in a target area; step S2, using the collapse-related data to construct an integrated collapse data database for the target area; step S3, labeling and classifying the data in the integrated collapse data database, dividing them into collapse occurrence data, collapse non-occurrence data and variable data, and forming a sample data set; step S4, based on the sample data set, using iterative reweighted least squares method to train a logistic regression model for road collapse risk assessment in the target area; step S5, using the trained logistic regression model, combined with relevant information of detected collapse hazards, to detect and assess the collapse risk of collapse hazards. The present invention can systematically, accurately and quickly assess the collapse risk of detected collapse hazards, and well meet the actual urban road collapse disaster risk assessment needs.

The application relates to the technical field of point cloud data processing, and specifically discloses a UAV point cloud original piece data processing system with a grading naming function; the system comprises the following modules: a boundary division module generates a rectangular boundary suitable for a terrain and screens a to-be-graded original piece; a grading identification module constructs geometric constraints based on a projection distance, completes tower distribution through extreme value judgment and parallel scene processing rules; a naming adaptation module integrates multi-source data to construct a scene feature vector, divides a risk range through clustering, realizes differential naming by adopting multi-source filling and normalization sorting; a feedback checking module locates a preferential analysis interval through deviation analysis, constructs a space neighborhood group and judges a high-risk area, and replaces an original algorithm to complete grading renaming and closed-loop checking by adopting a space index-hash mapping method; the application realizes dynamic optimization of point cloud grading naming, improves grading precision and naming compliance, and provides data support for power transmission line operation and maintenance.

The invention discloses a method for measuring preheating of a laser indirect driving pellet M belt, and belongs to the technical field of inertial confinement fusion diagnosis. The method comprises the steps that a black cavity, a toroidal bent crystal and a recording surface are arranged according to the Bragg imaging relation, diagnosis holes forming a 180-degree normal included angle are formed in the centers of the two side walls of the black cavity, a multi-layer-structure target ball is placed in the center of the black cavity and sequentially comprises a solid ball, a fluorescent layer, a foam layer and an ablation layer from inside to outside, and a shielding cone is assembled in the direction of the diagnosis hole in one side; the laser is converted into a Planck spectrum and an M band after being emitted into the black cavity, the M band penetrates through the ablation layer and the foam layer to induce the fluorescent layer to generate characteristic fluorescence, and the characteristic fluorescence is emitted out through the shielding cone and forms a monoenergetic fluorescence image on a recording surface after being diffracted by the toroidal curved crystal Bragg. Because the fluorescence intensity is in direct proportion to the intensity of the M belt, the preheating intensity and spatial distribution of the M belt of the pellet can be accurately obtained through the image. According to the method, targeted measurement of M-belt preheating is realized, the measurement precision is high, the repeatability is high, and key data support is provided for pellet compression efficiency evaluation in inertial confinement fusion research.

The invention discloses an information processing method and device for extracting anorectal pressure frequency domain characteristics, equipment and a medium, relates to the technical field of medical instruments, is applied to a computer device and is used for receiving original pressure information of various anorectal channels at different acquisition time points, and the original pressure information is acquired by an anorectal pressure measuring catheter; integrating the original pressure information of various anorectal channels under a target analysis time window to obtain a time domain pressure signal; performing short-time Fourier transform on the time domain pressure signals to obtain power spectral density of the pressure signals of various anorectal channels in the target analysis time window; and based on a target frequency band corresponding to the target analysis time window, extracting frequency domain features related to anorectal physiological functions from the power spectral density. And the frequency domain characteristics in anorectal pressure measurement are accurately extracted.

The invention discloses a label recommendation and exercise prescription generation system based on an exercise action library, which comprises an exercise action library, an exercise prescription summarization system, a patient health monitoring system and an exercise ability evaluation system, and is characterized in that the exercise prescription summarization system is connected with the patient health monitoring system and the exercise ability evaluation system; a big data module, an experience collection module and an artificial intelligence module are connected between the exercise prescription summarization system and the exercise action library, and the exercise action library is connected with a suitable crowd labeling module and an exercise intensity labeling module. According to the label recommendation and exercise prescription generation system based on the exercise action library, the requirements of patients are accurately matched, and scientificity, reliability, effectiveness and pertinence of exercise prescriptions are comprehensively ensured in multiple aspects; rich action libraries and exercise prescription libraries are provided, so that the exercise prescription making cost of doctors is reduced, and the working efficiency is improved; various motion scenes and flexible motion modes are provided for the patient.

The application discloses a kind of crop planting layout optimization methods.The optimization method includes: obtaining flood simulation data, farmland inundation data, future climate scenario data and crop-related parameters;Determine the key indicators of crop planting layout optimization, the key indicators include crop planting area and crop type spatial allocation;The constraint condition of crop planting layout is constructed, wherein the constraint condition includes constructing crop climate suitability constraint, constructing resource and safety constraint, and constructing space and flood risk constraint;Flood simulation data, farmland inundation data, future climate scenario data and crop-related parameters are imported into the constraint condition, and optimization parameters are generated based on the key indicators and the preset multi-objective intelligent optimization algorithm, and the optimization parameters form the crop planting layout optimization scheme.The technical scheme of the application can effectively meet the climate adaptability and risk prevention and control needs of agricultural production in flood-prone areas.

The invention relates to the field of decoration material preparation, in particular to a manufacturing method for producing a decoration material from construction waste, which comprises the following steps: acquiring a preset component image of a target forming component; determining a region analysis mode according to the proportion of the intaglio region of the preset component image; determining a quality detection mode according to whether the preset component image of the target forming component has the intaglio pattern or not, wherein the quality detection mode is ultrasonic detection or radiographic detection for the target forming component; according to the coincidence coefficient of the abnormal quality area and the intaglio area of the target forming component, a preparation adjusting strategy of the target forming component is determined, and the preparation adjusting strategy is used for adjusting the preparation grinding duration or the exciting agent mixing amount. And therefore, the effectiveness of the adjusting mode of the preparation process of the target forming component is improved.