199 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 a safe and rapid evaluation treatment method for overlying strata water diversion under working face mining, in the treatment method, before working face stoping, a waterproof curtain is constructed along the boundary of a surface subsidence range, the waterproof curtain extends into a bottom water-resisting layer from the surface, so that the waterproof curtain is constructed along the vertical projection direction; and the bottom aquifer in the surface subsidence range is completely sealed by the waterproof curtain, so that water inside and outside the waterproof curtain does not interfere with each other, and the water volume influencing the stoping of the working face is reduced. A plurality of water level and crack monitoring assemblies are arranged at the same time, in the stoping process of the working face 1, the water level condition in a waterproof curtain and the crack condition generated by sinking of a bottom waterproof layer are monitored in real time through the water level and crack monitoring assemblies, and corresponding treatment measures are taken according to the corresponding conditions; the waterproof curtain, the grouting operation and the water pumping operation cooperate with one another, the effect that no water is stored in the waterproof curtain is achieved, meanwhile, the construction cost can be greatly reduced, the construction efficiency is improved, and the ecological environment is protected.

Ther present invention provides a technique for evaluating high-speed motion included in an operation of a processing unit. Firstly, a specific operation of the processing unit is shot by an event-based camera. In this way, event data is acquired, which includes information about only pixels whose luminance values have changed. Then, an evaluation value is calculated based on the event data. Thereafter, the specific operation of the processing unit is evaluated in accordance with the calculated evaluation value. The event data has recorded therein information about high-speed motion included in the specific operation of the processing unit. Accordingly, it is possible to evaluate the high-speed motion in accordance with the evaluation value.

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 three-dimensional model-based complex architecture power grid service system operation state identification method. The method comprises the following steps of: 1, constructing a visual three-dimensional model from department services to system physical facilities by using a three-dimensional visualization technology; 2, on the basis of a multi-dimensional information layered drilling dynamic display technology, presenting a relationship between layers in the three-dimensional model, and displaying an association relationship and an affiliation relationship between elements; 3, performing automatic rendering construction on the three-dimensional model by utilizing a visual element layout algorithm; a topological graph is automatically generated, and an end-to-end system simulation visualization platform is formed; and 4, identifying the operation state of the power grid service system. According to the method, a standard is provided for display and operation monitoring of a'one-picture 'system for panoramic penetration of the service system, the interactive and linkable interface display effect is improved, managers are promoted to clearly understand the system, service application evaluation treatment is assisted, and a technical means is provided for supporting next service application operation.

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 embodiment of the invention provides a micro-service interface management method and device, electronic equipment and a storage medium, belongs to the technical field of computers, and is suitable for the field of finance. The method comprises the following steps: performing registration processing on the front-end gateway to obtain configuration information; performing programming language recognition processing on the micro-service unit according to the configuration information to obtain a programming language recognition result; performing interface capture processing on the micro-service unit according to the programming language recognition result to obtain a micro-service interface; and performing reusability evaluation processing on the micro-service interface, and performing unified management on the micro-service interface according to a reusability evaluation result. The embodiment of the invention can improve the management efficiency of the micro-service interface, and can be widely applied to the technical field of computers.

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 discloses an impact resistance evaluation method and device for a double-phase structure. The method comprises the following steps: obtaining a performance index set of the double-phase structure; the performance index set comprises a plurality of performance index subsets; each performance index subset comprises acquisition sequence values of a plurality of parameters; utilizing the performance index set to construct an anti-impact index numerical matrix; and carrying out comprehensive evaluation processing on the impact resistance index numerical value matrix to obtain an impact resistance evaluation value. According to the method, the problem that the impact resistance of the material in practical application is difficult to accurately predict due to the fact that existing evaluation methods mostly depend on empirical formulas or qualitative analysis is solved.

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 invention relates to the technical field of medical instruments, and discloses a cardiac pacemaker multi-mode communication system which comprises a data acquisition module and a communication management module. According to the system, electrical activity signals of the heart of a user at all time points, specification data of all hardware of the cardiac pacemaker and all communication modes of the cardiac pacemaker are acquired through a data acquisition module and are classified to form a data set, and a communication management module analyzes and generates an abnormal data set and then judges whether electric pulses are sent to stimulate cardiac muscle contraction or not; if data exists in the abnormal data set, the corresponding pulse intensity is analyzed and generated, and the magnitude of current of different intensities in different application scenes is converted into the pulse quantity, so that the standardized evaluation treatment effect is good, and the adjustment difficulty between pacemakers of different models is reduced; and the authority level of the interconnection application is judged according to the application source, the communication mode corresponding to the cardiac pacemaker is started, and the rapid response interconnection transmission efficiency is high.

To provide an image processing system, an image processing method and an image processing program capable of reducing a throughput of recognition processing to a prescribed item of an input image and improving recognition accuracy.SOLUTION: A detection processing part 113 detects a specific character string of a related item related to a detection object out of character strings included in an image and recognized as characters. An evaluation processing part 114 calculates evaluation values of other character strings, on the basis of a position of the specific character string in the image, and positions of other character strings except for the specific character string in the character strings. An output processing part 116 outputs a character string which is identified on the basis of the evaluation value calculated by the evaluation processing part 114 out of other character strings, as a character string to be detected.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.