162 results about "Evaluation treatment" patented technology

The invention discloses a method and a device for evaluating the performance of an automatic and rapid unfolding and folding tent. The method comprises the following steps: acquiring a performance index test data set of the automatic and rapid unfolding and folding tent; the performance index test data set comprises an unfolding and folding type index test data set, an efficiency type index test data set and an environment adaptation type index test data set; each type of index test data set comprises a plurality of types of index test data sequences; preprocessing the performance index test data set to obtain a preprocessed data set; performing classification evaluation processing on each type of index test data set in the preprocessed data set to obtain a sub-index test value set; and performing fusion evaluation processing on the sub-index test value set to obtain a performance evaluation result value of the automatic rapid unfolding and folding tent.

Provided in the present application are a text processing method and apparatus based on artificial intelligence, and an electronic device, a computer program product and a computer-readable storage medium. The present application can be applied to the field of artificial intelligence and the field of large models. The method comprises: acquiring first integrated text, wherein the first integrated text is obtained by means of correcting first original text; splicing the first integrated text and the first original text to obtain spliced text; performing multi-dimensional evaluation processing on the spliced text to obtain an evaluation result corresponding to each dimension, wherein the multi-dimensional evaluation processing comprises at least two of the following: semantic evaluation processing, grammar evaluation processing and typesetting evaluation processing; and fusing evaluation results of at least two dimensions to obtain a correction evaluation result of the first integrated text.

The invention provides an array hospital decision processing method and system based on big data. The method comprises the following steps: collecting and comprehensively analyzing dynamic data streams from a plurality of battlefield medical sites in real time, and generating a virtual medical resource thermodynamic diagram; based on the virtual medical resource thermodynamic diagram, a particle swarm optimization algorithm is adopted to perform intelligent planning processing on a sick and wounded evacuation path and a medical material allocation scheme, and a sick and wounded evacuation and resource allocation plan is generated; the sick and wounded evacuation and resource configuration plan is utilized, the effectiveness of a current treatment strategy is evaluated by applying a support vector machine algorithm, and a risk early warning and response scheme is generated; and according to the prospective decision support report and the risk early warning and countermeasure scheme, establishing a cloud cooperative working platform, and generating an efficient communication channel and an information security guarantee mechanism. According to the technical scheme provided by the invention, the ability and flexibility of a position hospital to deal with emergencies are remarkably improved.

The present invention discloses a performance evaluation method and device for an automatic and rapid deployment and retraction tent. The method comprises: collecting a performance index test data set for the automatic and rapid deployment and retraction tent; the performance index test data set comprises an deployment and retraction index test data set, an efficiency index test data set, and an environmental adaptability index test data set; each type of index test data set comprises several types of index test data sequences; preprocessing the performance index test data set to obtain a preprocessed data set; performing classification evaluation processing on each type of index test data set in the preprocessed data set to obtain a sub-index test value set; and performing fusion evaluation processing on the sub-index test value set to obtain a performance evaluation result value for the automatic and rapid deployment and retraction tent.

The invention provides an intelligent evaluation method and system for rental asset recovery and a medium. The method comprises the steps of obtaining equipment basic information data of target mobile equipment, performing evaluation processing, obtaining equipment preliminary recovery value evaluation data, collecting appearance image information of the target mobile equipment, extracting appearance condition feature data, performing processing according to the appearance condition feature data, obtaining an equipment appearance value evaluation index, and obtaining a recovery value evaluation result of the target mobile equipment. Obtaining hardware performance characteristic data of the target mobile equipment, processing to obtain an equipment hardware performance depreciation index, obtaining use behavior characteristic data of the target mobile equipment, processing to obtain an equipment depreciation index, and evaluating the data according to the initial recovery value of the equipment; processing is carried out in combination with an equipment appearance value evaluation index, an equipment hardware performance loss index and an equipment depreciation degree index, and final recovery value evaluation data of the equipment is obtained, so that the lease asset recovery intelligent evaluation technology is realized.

The invention relates to the technical field of digital art design. According to the digital art design assisting method and system based on artificial intelligence, the method comprises the steps that multi-dimensional feature extraction processing is conducted on generated art works, and a comprehensive feature matrix is generated; performing quantitative evaluation processing through a dynamic weighted scoring model to generate a comprehensive score of the current work; performing clustering grouping processing through a diversity protection mechanism to generate a representative work set; performing diversity index calculation processing on the representative work set to generate diversity index data; performing element extraction processing through a historical recall mechanism to generate a fusible creation element set; performing fusion creation processing through a genetic algorithm to generate a mixed creation scheme; and carrying out feedback evaluation processing on the mixed creation scheme to generate system optimization parameters so as to achieve the technical effects of improving the dynamic adaptability of work value evaluation, reducing the creation homogenization risk and improving the fusion creation efficiency.

The invention provides an industrial fault multi-scheme generation method and system fused with a knowledge graph, and the method comprises the steps: obtaining a fault data set of target industrial equipment, carrying out the feature extraction processing, generating a fault feature set, calling a pre-constructed industrial knowledge graph, carrying out the entity association analysis processing, and generating a fault association feature set; fault propagation path reasoning processing is carried out based on the fault correlation feature set, a potential fault propagation path set is generated, then solution matching and feasibility evaluation processing are carried out on the potential fault propagation path set, and finally an optimized solution set is generated, so that professional knowledge in the industrial field is fused; fault propagation paths can be accurately analyzed, diversified and optimized solutions can be generated, and the accuracy of industrial fault diagnosis and the effectiveness of the solutions are improved.

The invention relates to the technical field of data processing, and discloses a cross-scale spectrum and chromatographic data associated pollutant conversion evaluation method and system. The method comprises the following steps: collecting reaction parameters through multi-point sensing, and normalizing spectrum and chromatographic data to obtain a characteristic matrix; decomposing and fusing data of different scales by utilizing a multi-layer association tensor to form a structure-activity relation graph; based on the map, constructing a corresponding rule by using a deep self-attention neural network, and generating a degradation efficiency predictor; and the optimal scheme report card is formed according to the predictor evaluation processing parameters. According to the application, accurate prediction and optimization of the degradation process of the organic pollutants in the coal gangue / persulfate system are realized, the number of experiments is reduced, and the scientificity and high efficiency of treatment scheme design are improved.

The invention discloses a data classification evaluation method for sewage monitoring based on big data, and relates to the technical field of data processing. The data classification evaluation method for sewage monitoring based on big data comprises the following steps: dividing a total sewage monitoring area; performing concentration threshold contrastive analysis on the original data; performing second classification adjustment according to the second comparative analysis result; and performing third classification adjustment according to the third comparative analysis result. According to the method, first classification evaluation and second classification evaluation are performed on different data acquisition point locations according to an early warning result; performing second classification adjustment according to the second comparative analysis result; according to the third comparative analysis result, third classification adjustment is carried out, the effect of improving the accuracy of classification evaluation processing of the original data of sewage monitoring is achieved, and the problem that in the prior art, the accuracy of classification evaluation processing of the original data of sewage monitoring based on big data is insufficient is solved.

The invention belongs to the technical field of testing, and particularly relates to a multi-pollutant co-processing monitoring system of desulfurization equipment. The system comprises a processor, a desulfurization effect monitoring module, an equipment operation feedback module, a matching judgment module, a preprocessing analysis module and a regulation and control optimization module. The desulfurization effect monitoring module synchronously collects sulfur and nitrogen oxide content and dust concentration data in tail gas, the treatment effect is evaluated through a comprehensive deviation value, and the equipment operation feedback module calculates the equipment comprehensive treatment capacity value in combination with operation data of an air compressor and a slurry pump. The matching judgment module evaluates the matching degree of the processing capacity and the multi-pollutant load and generates a regulation and control signal, the preprocessing analysis module evaluates the preprocessing effect and generates an optimization instruction, the regulation and control optimization module generates an optimal regulation and control parameter set based on a multi-target optimization algorithm, and the processor dynamically adjusts a weight threshold and executes fault diagnosis. And comprehensive evaluation and cooperative regulation and control of the sulfur, nitrogen oxide and dust treatment effect are realized.

The invention provides a quality control predictive analysis method and platform, and belongs to the technical field of predictive evaluation, and the method specifically comprises the steps: carrying out the evaluation processing of the quality score of an updated credit model in a predictive analysis period, so as to update the evaluation analysis results of the quality scores of the updated credit model in different predictive analysis periods, according to the control method for determining the model quality of the credit loan model, the matching condition of the credit loan model in a prediction analysis period between different update processing times is combined with the control method for the model quality of the credit loan model with different update processing times. And a prediction analysis method for quality control after the next update processing of the credit model is determined, so that the model quality of the credit model after the update processing is improved.

The invention discloses an intelligent evaluation method and device for multi-modal test data. The method comprises the following steps: acquiring a multi-modal test data set in an equipment performance test process; the multi-modal test data set comprises a multi-source data subset of each technical index measured in an equipment performance test process; preprocessing the multi-modal test data set to obtain a preprocessed data set; performing fusion evaluation on the multi-source data subset of each technical index in the preprocessed data set to obtain an evaluation value of each technical index; and performing comprehensive performance evaluation processing on the evaluation values of all the technical indexes to obtain a test evaluation value of the equipment performance. According to the intelligent evaluation method, weight distribution can be flexibly adjusted according to the characteristics of different technical indexes, so that the accuracy and reliability of an evaluation result are remarkably improved, and powerful support is provided for comprehensive evaluation of equipment performance.

The embodiment of the invention provides a multi-agent data governance method and system based on negative feedback optimization, and the method comprises the steps: carrying out the data governance of to-be-governed data based on a multi-agent system, obtaining a data governance result, and creating a task execution path map in a data governance process in real time, based on a preset evaluation index set and a dynamic threshold set, performing evaluation processing on the data governance result to obtain negative feedback data, querying a task execution path map according to the negative feedback data to obtain a task processing path, and performing evaluation processing on the task processing path to obtain one or more to-be-optimized agents, and performing matching processing based on the negative feedback data, the task type of the to-be-optimized agent and the optimization parameter matching library to obtain corresponding optimization data, performing optimization of the corresponding to-be-optimized agent according to the optimization data, and performing data management of the to-be-managed data again based on the optimized multi-agent system. According to the scheme, the intelligent agent can be optimized and iterated based on a negative feedback learning mechanism.

The invention relates to the field of industrial equipment anomaly detection, in particular to a slaughter line anomaly identification method and system based on digital twinning, and the method comprises the steps: carrying out the operation data collection and health reference data collection of a splitting saw in a slaughter line through a data collection unit and a digital twinning interface unit; performing digital twinborn reference correction and accumulation on instantaneous current data of a driving unit and performing control chart anomaly detection processing to obtain a preliminary anomaly judgment result of the operation state of the splitting saw; carrying out fusion evaluation processing on the physical characteristic data and the health reference data of the splitting saw to obtain an abnormal source tendency discrimination factor; the preliminary abnormity judgment result and the abnormity source tendency judgment factor are comprehensively analyzed to obtain the abnormity identification result of the current processing period of the splitting saw, so that the equipment abnormity identification accuracy in the slaughter line is improved.

The invention discloses a puzzle solution game adaptive design method and system based on ecological balance, and the method specifically comprises the steps: receiving ecological scene data selected by a player, carrying out the evaluation processing of the capability level of the player through combining with a player capability evaluation model, and generating an evaluation result; dynamically generating hierarchical ecological problems according to an evaluation result, and synchronously activating Agent behavior tree loaders of corresponding hierarchies to form an Agent modeling system; simulating a biological interaction network through an Agent modeling system, inputting real-time operation data of the biological interaction network into an LSTM double-time-sequence prediction engine for prediction processing, and generating an ecological evolution graph; and generating a dynamic visual interface according to the ecological evolution map, and triggering a difficulty regulator when detecting that the ecological imbalance index exceeds a difficulty threshold value of the current player. Complex characteristics of an ecological system are effectively simulated, more challenging and interesting puzzle solving game experience is provided for players, and meanwhile understanding and protection awareness of the players to the ecological system can be improved.

The invention relates to the technical field of teenager physical health management, and discloses a teenager physical health management system based on physical test results, and the system comprises a data collection terminal, a health intervention device and a cloud management platform which are in communication connection. The data collection terminal collects teenager physical test motion indexes and physiological signals in real time, and the health intervention device receives an instruction of the cloud management platform to adjust the training intensity. The data monitoring unit records an index abnormal starting point and a recovery termination point to determine a health risk interval, and controls the equipment to operate at a safety threshold and generate a physical characteristic curve for physical prediction mapping; the evaluation processing unit corrects the intervention path to generate an execution strategy; and a conventional regulation and control unit and an emergency regulation and control unit of the health management unit control equipment to execute corresponding operation under normal and abnormal working conditions respectively. According to the system, real-time monitoring, accurate evaluation, scientific intervention and risk processing of teenager physical health are realized, teenager physical test safety is effectively guaranteed, and the physical health condition is improved.

The invention discloses a number-real combined simulation evaluation method and device for unmanned cluster performance. The method comprises the following steps: acquiring a performance actual test result information set and a performance simulation test result information set of an unmanned cluster; the performance actual test result information set comprises an actual test result value sequence of each performance index of the unmanned cluster; the performance simulation test result information set comprises a simulation test result value sequence of each performance index of the unmanned cluster; preprocessing the performance actual test result information set and the performance simulation test result information set to obtain a preprocessed information set; and performing comprehensive performance evaluation processing on the preprocessed information set to obtain a comprehensive performance evaluation value of the unmanned cluster.

The embodiment of the invention provides a model parameter determination method and device, a storage medium and a program product, and the method comprises the steps: processing input data through employing a specified model, so as to generate at least one piece of thinking process information and corresponding answer information, and at least part of the thinking process information corresponds to a plurality of pieces of answer information; performing evaluation processing on the input data based on at least part of the answer information to determine corresponding optimization feedback information; updating at least one parameter of the specified model according to the optimization feedback information; wherein the specified model is a visual language model or a large language model, and the input data comprises at least one of text data, image data and point cloud data. Through multi-answer sampling, optimization feedback of more answer levels can be obtained under the condition that the generation number in the thinking process is reduced or is kept unchanged, so that the training time and the calculation overhead are remarkably reduced, the training efficiency is improved, and the thinking and summarization ability of the model can be improved under limited calculation resources through a training scheme after reinforcement learning.

The invention discloses a laparoscopic surgery skill assessment method based on surgical instrument movement and a related device, and the method comprises the steps: obtaining a to-be-assessed laparoscopic surgery video, and carrying out the frame extraction processing, and forming a to-be-assessed video frame sequence image; inputting the to-be-evaluated video frame sequence image into a medical instrument motion feature extraction model to carry out motion feature extraction processing corresponding to the plurality of medical instruments in the laparoscopic surgery process, and obtaining multi-modal motion features corresponding to the plurality of medical instruments; performing cross-modal feature construction processing on the multi-modal motion features and preoperative clinical indexes of the patient to obtain cross-modal feature data; and inputting the cross-modal feature data into the XGBoost-SHAP combined framework, and performing evaluation processing to obtain an evaluation result corresponding to each feature in the cross-modal feature data. In the embodiment of the invention, the interpretability of instrument motion feature-surgical skill evaluation is realized, and the clinical applicability of the final scoring model can be improved.

The invention discloses a vulnerability assessment processing method and device, equipment and a medium. The vulnerability assessment processing method comprises the steps of determining a feature initial weight of a vulnerability assessment equation according to vulnerability sample data to be analyzed and a linear regression model, and performing fine adjustment on the feature initial weight based on a random forest model to obtain a feature stable weight; generating a vulnerability assessment target equation according to the feature stability weight and a vulnerability assessment equation; and obtaining an SOAR target script, and performing vulnerability merging and work order distribution according to the SOAR target script and the vulnerability assessment target equation. According to the technical scheme provided by the embodiment of the invention, the application effect of the vulnerability evaluation result and the distribution efficiency of the work order generated by the vulnerability evaluation result can be improved.

To provide a goods management system, goods management method, and goods management program capable of arranging picking target goods in optimal positions.SOLUTION: A management server 1 includes an acquisition processing unit 112 for acquiring individual picking processing times in cases where multiple goods are placed at each of multiple placement positions; a prediction processing unit 113 for acquiring picking prediction information for the goods; an evaluation processing unit 114 for evaluating combination picking processing times corresponding to multiple placement position combinations based on the individual picking processing times and picking prediction information; and a determination processing unit 115 for determining one placement position combination from the multiple placement position combinations based on the combination picking processing times.SELECTED DRAWING: Figure 1

The embodiment of the application provides a multi-agent data governance method and system based on negative feedback optimization, which comprises the following steps: performing data governance on to-be-governed data based on a multi-agent system to obtain a data governance result, and creating a task execution path atlas in real time during data governance; performing evaluation processing on the data governance result based on a preset evaluation index set and a dynamic threshold set to obtain negative feedback data; querying the task execution path atlas according to the negative feedback data to obtain a task processing path; performing evaluation processing on the task processing path to obtain one or more to-be-optimized agents; performing matching processing based on the negative feedback data, a task type of the to-be-optimized agent and an optimization parameter matching library to obtain corresponding optimization data; performing optimization on the corresponding to-be-optimized agent according to the optimization data; and performing data governance on the to-be-governed data based on the optimized multi-agent system. The scheme can optimize and iterate the agent based on a negative feedback learning mechanism.

The invention provides a building damage degree assessment method, device and equipment. The building damage degree assessment method comprises the steps of obtaining visual data reflecting the building damage degree in a first scene; obtaining priori knowledge data related to the building damage degree in the second scene; the visual data are input into a first classifier for building damage degree classification processing, a first classification result is obtained, and the first classifier is obtained through training of a first preset model; the knowledge data is input into a second classifier for building damage degree classification processing, a second classification result is obtained, and the second classifier is obtained through training of a second preset model; and inputting the first classification result and the second classification result into a fusion model to carry out building damage degree evaluation processing to obtain a building damage degree evaluation classification result. According to the invention, the accuracy of building damage degree classification can be improved.

The invention provides an enterprise management method and system and computer equipment, and the method comprises the steps: determining initial enterprise data of a plurality of enterprises and a corresponding enterprise management strategy, carrying out the preprocessing of the initial enterprise data, obtaining target enterprise data, generating an enterprise global database, and carrying out the calculation of the enterprise global database according to the enterprise management strategy. Determining at least one target evaluation algorithm and a corresponding service providing strategy, and based on each target evaluation algorithm, according to the target enterprise data of the plurality of enterprises in the enterprise global database, performing evaluation processing on the development conditions of the plurality of enterprises to obtain an enterprise development condition evaluation result corresponding to each target evaluation algorithm, and providing a service matched with the development condition of the target enterprise for the target enterprise based on the enterprise development condition evaluation result and the service providing strategy corresponding to each target evaluation algorithm. Therefore, operation complexity of enterprise management is reduced, timeliness and accuracy of service providing and enterprise management are improved, enterprise satisfaction is improved, and corresponding management of multiple enterprises is facilitated.

This application relates to the field of biomedical engineering technology. This application discloses a method, device, terminal device and storage medium for dual-foot sole video evaluation based on plantar perfusion imaging, which can improve the accuracy of evaluation results, simplify the measurement process and enhance the patient experience. The method includes obtaining a dual-foot sole video; obtaining a plurality of left plantar rPPG signals and a plurality of right plantar rPPG signals based on the dual-foot sole video; drawing a plurality of dual-foot sole perfusion maps based on the plurality of left plantar rPPG signals and the plurality of right plantar rPPG signals; generating a target image based on the plurality of dual-foot sole perfusion maps; extracting the average value, standard deviation, maximum value and minimum value of the blood perfusion index ratio from the target image and inputting them into a classifier for evaluation processing to obtain an evaluation result, and medical staff refer to the evaluation result to diagnose peripheral artery disease and its severity.

The invention provides an evaluation processing method and device for product development, equipment and a storage medium, and relates to the field of product development. The method comprises the steps of obtaining first data of a to-be-developed product and second data of the to-be-developed product; generating a demand decomposition tree according to the first data; generating a function network according to the second data; according to the first data and the second data, distributing the demand decomposition tree to an analysis node to obtain a demand function association network; generating a demand engineering analysis result, a design failure mode and an influence analysis result corresponding to the analysis node according to the demand function association network; and displaying a demand engineering analysis result, a design failure mode and an influence analysis result corresponding to the analysis node on a preset display interface. The technical problem that in the prior art, demand management, design failure modes and influence analysis are independent, definition deviation, feedback delay and work repetition are prone to occurring, and then the evaluation processing efficiency of product development is low is solved.

The data processing method and device provided in the application relate to the technical field of data analysis. The data processing method can accurately match the main business information of the enterprise to be warehoused with the green industry type in the green enterprise database, and then, the reliability of the class label corresponding to the matching degree of the enterprise to be warehoused and the corresponding green industry type is also high. In this way, when the project to be evaluated needs to be evaluated, the evaluation rule corresponding to the category of the project to be evaluated can be obtained from the database according to the class label, so as to evaluate the project to be evaluated. Since the evaluation rule matches the project to be evaluated, the accuracy is high and the efficiency is high.

The present application discloses a non-perceptual lightweight three-dimensional data processing method, device, and storage medium, relating to the technical field of three-dimensional data processing. The non-perceptual lightweight three-dimensional data processing method includes: obtaining key feature information of pre-processed three-dimensional model data, and performing importance evaluation processing on the key feature information based on a graph theory algorithm to obtain an importance score of the key feature information; after removing the key feature information whose importance score is less than a preset score, performing data simplification processing on the key feature information based on a preset simplification algorithm; determining a compression strategy based on the data type of the three-dimensional model data, and after encoding the three-dimensional model data, compressing the encoded data based on the compression strategy to obtain compressed data. Performing dimensionality reduction and simplification processing on the three-dimensional data based on the importance score of the key feature information improves data processing efficiency.

The application discloses a GNSS quality control method based on INS / ODO assistance and a storage medium. First, an evaluation process of a positioning scene in which a GNSS receiver is located is performed, and evaluation scores of the positioning scene of multiple indexes are output. The evaluation scores of each positioning scene are sorted, and the positioning scene with the highest evaluation score is recorded as a target positioning scene of the GNSS receiver at a current epoch. A processing operation of estimating accuracy, calculating error and dynamically adjusting the STD value of the GNSS positioning result at the current epoch is performed. The above method collects and deeply analyzes a large amount of experimental data, and accurately counts precision parameters related to lock loss time and lock loss distance under the condition that the GNSS / INS / ODO combined navigation is lost. The precision parameters are used as algorithm inputs, and can be flexibly adjusted according to the precision level of different inertial modules, so that the adaptability and universality of the system are significantly improved.

The invention provides a building investment consultation data analysis processing method and system, and belongs to the technical field of data processing. When it is determined that real-time updating processing of the investment consultation project does not need to be performed in the database of the type of the building, determining an updating strategy of a change item of the construction amount of the investment consultation project on the basis of the similar situation of the construction project of the estimation deviation type in the database of the investment consultation project of estimation change; on the basis of the updating strategy of the change item of the construction amount of the investment consultation project, whether the construction drawing data of the investment consultation project needs to be recognized or not when the investment consultation project of the database of the building of the type is updated is determined, and the reliability degree of evaluation processing of the project amount is improved.