115 results about "Evaluation treatment" patented technology

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 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 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.

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 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.

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 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.

The application relates to the field of artificial intelligence and discloses a text connotation quality evaluation method for improving the accuracy of text connotation quality evaluation and improving model training efficiency. The text connotation quality evaluation method comprises the following steps: obtaining an initial text from a preset medical record text; processing the initial text through a natural language processing algorithm to obtain a target text; performing text coding on the target text through a preset bag-of-words model and a preset automatic coding model to obtain first text features; performing feature extraction on the target text to obtain second text features, wherein the second text features comprise text complexity features, text grammar style features and medical semantic features; performing evaluation processing on the first text features and the second text features through a trained logistic regression model to obtain an evaluation result, wherein the evaluation result is used for identifying the connotation quality grade of the preset medical record text. The application also relates to the blockchain technology, and the target text is stored in the blockchain.

The invention discloses a feedback type lung rehabilitation evaluation therapeutic apparatus, and relates to the technical field of medical instruments, the feedback type lung rehabilitation evaluation therapeutic apparatus comprises a bicycle assembly, the bicycle assembly is connected with an expiration mask and a detection bracelet, the detection bracelet sleeves the wrist of a patient, the expiration mask is worn at the mouth and nose position, and the bicycle assembly is provided with a sensor and a resistance assembly. The resistance assembly is controlled through the central processing unit, a data acquisition module is arranged on the expiration mask, the data acquisition module acquires the respiratory rate of a patient, and then the heart rate of the patient is controlled by controlling the resistance of the bicycle assembly. According to the technical scheme, the resistance of the bicycle assembly can be detected in real time through the sensor assembly, then evaluation is conducted through the respiratory rate and the heart rate detected by the detection bracelet, and then the resistance is controlled through the central processing unit so that a patient can achieve the stable respiratory rate and heart rate.

The present invention provides a quality control prediction and analysis method and platform, which belongs to the field of prediction and evaluation technology, and specifically includes: evaluating the quality score of the credit model after the update processing in the prediction and analysis period, determining the model quality control method of the credit model based on the evaluation and analysis results of the quality score of the updated credit model in different prediction and analysis periods, determining the prediction and analysis method for quality control of the credit model after the next update processing based on the matching of the prediction and analysis periods between different update processing times of the credit model, and combining the model quality control method of the credit model at different update processing times, thereby improving the model quality of the credit model after the update processing.

This application relates to a device control method, apparatus, device, and system based on behavior monitoring. The device control method based on behavior monitoring includes: extracting features from behavior monitoring data of a target object to obtain behavior features; performing a first behavior evaluation process on the behavior features to obtain a first evaluation result; performing a second behavior evaluation process on the behavior features to obtain a second evaluation result; identifying the target behavior state of the target object based on the first and second evaluation results; and adjusting the device in the space where the target object is located based on the target behavior state. This solution can improve the intelligence level of the device control process.

The invention discloses a directional cognitive ability assessment method and device based on virtual reality. The system comprises a universal treadmill, a motion measurement module, a virtual reality helmet, an olfactory electroencephalogram module, a directional cognitive ability assessment module and a monitoring module. The universal treadmill, the motion measurement module, the virtual reality helmet and the monitoring module are connected with the directional cognitive ability evaluation module; the monitoring module is used for collecting and processing physiological signals of a user to obtain a collected information set; and the directional cognitive competence evaluation module is used for evaluating the motion track information of the legs of the user, feedback information of the directional cognitive test information and the like to obtain directional cognitive competence evaluation result information of the user. The universal treadmill is introduced, various psychological and physiological indexes of the user are collected while the user completes the virtual directional cross-country activity, measurement information capable of reflecting the real directional cognitive ability of the user is obtained, and it is guaranteed that the evaluation result is objective and accurate.

The present invention discloses a data classification and evaluation method for sewage monitoring based on big data, which relates to the field of data processing technology. The data classification and evaluation method for sewage monitoring based on big data includes the following steps: dividing the total sewage monitoring area; performing concentration threshold comparative analysis on the original data; performing a second classification adjustment based on the second comparative analysis result; and performing a third classification adjustment based on the third comparative analysis result. The present invention performs a first classification evaluation and a second classification evaluation on different data collection points based on the early warning results; performs a second classification adjustment based on the second comparative analysis result; and performs a third classification adjustment based on the third comparative analysis result, thereby achieving the effect of improving the accuracy of the classification and evaluation processing of the original data of sewage monitoring, and solving the problem of insufficient accuracy of the classification and evaluation processing of the original data of sewage monitoring based on big data in the prior art.

The application discloses a laparoscopic surgery skill evaluation method based on surgical instrument motion and related devices, and the method comprises the following steps: obtaining a laparoscopic surgery video to be evaluated, and performing frame extraction processing to form a video frame sequence image to be evaluated; inputting the video frame sequence image to be evaluated into a medical instrument motion feature extraction model to perform motion feature extraction processing on a plurality of medical instruments in a laparoscopic surgery process, and obtaining a plurality of medical instrument corresponding multi-modal motion features; performing cross-modal feature construction processing on the multi-modal motion features and preoperative clinical indicators of a patient to obtain cross-modal feature data; inputting the cross-modal feature data into an XGBoost-SHAP joint framework, and performing evaluation processing to obtain evaluation results corresponding to each feature in the cross-modal feature data. In the embodiment of the application, the instrument motion feature-surgery skill evaluation is interpretable, and the clinical applicability of the final scoring model can be improved.

The invention relates to the technical field of robot control and the field of insurance business and smart medical treatment, and provides a robot control method and device, electronic equipment and a computer readable storage medium, and the method comprises the steps: obtaining a voice instruction and an initial observation image; performing visual reasoning processing based on a causal attention sub-module in a pre-trained visual language model, the voice instruction and the initial observation image to obtain a sub-target image; performing motion prediction processing based on a full attention sub-module, a voice instruction, an initial observation image and a sub-target image in a visual language model to obtain predicted motion sequence information; performing evaluation processing on the predicted action sequence information to obtain action evaluation information; and under the condition that the action evaluation information represents that the predicted action sequence information meets the preset condition, determining the predicted action sequence information as final action sequence information. Through the technical scheme, the task execution accuracy of the robot can be improved.

The invention discloses a learning ability evaluation method based on label aggregation and behavior analysis and a medium. Obtaining a current to-be-evaluated task and current joint description data; performing aggregation standardization processing on the multi-source tag description data through a tag aggregation processing method to obtain at least one current standardized tag; processing through a sub-label behavior trend analysis and calculation method to obtain each current weighted learning intensity index, a current behavior trend slope and a current behavior trend confidence coefficient; and obtaining and performing calculation processing through a sub-label capability difference value contribution degree calculation method according to a standard capability requirement to obtain and feed back a target sub-label capability difference value and a target sub-label difference value contribution degree so as to complete evaluation processing of the learning capability of the current to-be-evaluated task. The problems of label redundancy, poor ability evaluation accuracy, insufficient interpretability of the user ability development trend and poor flexibility are solved, and the accuracy, comprehensiveness and flexibility of ability evaluation are improved.

The invention discloses a gas safety evaluation method and system based on a simulation scene, a terminal and a storage medium, and the method comprises the steps: obtaining a gas safety evaluation task of a user, carrying out the analysis processing of the gas safety evaluation task, and obtaining a target analysis result; performing scene building according to the target analysis result to obtain a target gas simulation scene, and performing measure making on the target gas simulation scene to obtain scene protection measures; and performing safety test processing on the target gas simulation scene according to the scene protection measure to obtain a gas safety test result, and performing evaluation processing on the gas safety test result to obtain a gas safety evaluation result. According to the invention, the accuracy of a gas safety evaluation result is improved by perfecting a safety evaluation framework and providing a safety verification mechanism, so that the gas safety is improved.

The embodiment of the invention provides a user query processing method and device, equipment, a storage medium and a program product. The method comprises the steps that a scheduling agent is utilized, based on corresponding description information of a plurality of function blocks, a plurality of tasks for user query are determined, and at least one task in the tasks needs to call at least one function block in the function blocks; determining a first processing result for the user query based on corresponding execution results of the plurality of tasks obtained by using the execution agent; determining, using an evaluation agent, a processing state evaluation based on the respective execution results of the plurality of tasks, the processing state evaluation at least indicating whether the first processing result satisfies the user query; and determining, using the execution agent, a target processing result for the user query at least based on the processing state evaluation. In this way, the efficiency and accuracy of processing the user query can be improved.

A device includes one or more processors configured to obtain, at a primary orchestrator of a system, a notification of a change event from an authoritative source of the system and identify, based on an evaluation precedence network at the primary orchestrator, one or more evaluations to perform in response to the change event. For each identified evaluation, the processor(s) are configured to send, from the primary orchestrator, an evaluation request to a secondary orchestrator of the system to request performance of the evaluation, and receive, from the secondary orchestrator, an evaluation result based on performance of the evaluation. The processor(s) are configured to update the evaluation precedence network to indicate an updated state of evaluation executions based on one or more of the evaluation results. The processor(s) are configured to determine, at the primary orchestrator, whether to generate an additional evaluation request after the evaluation precedence network is updated.

The present application relates to a kind of community chronic disease auxiliary decision system, including knowledge warehouse end, value evaluation end and learning network end;Knowledge warehouse end provides the rule and constraint of disease treatment scheme;Value evaluation end provides the value index of evaluation treatment result, value includes treatment benefit, damage and cost;Learning network end is used for the collection and storage of patient state data, generates treatment scheme collection, obtains patient value collection, obtains the highest comprehensive value from multiple treatment schemes as decision scheme, predicts the possible treatment scheme of patient and the value generated by scheme, feedback to treatment scheme by value evaluation system, to obtain the recommended scheme order and its corresponding value.The above model is established application platform, and is tested and improved by community empirical research.The present application will provide technical tool for the standardized management of community medical institutions T2DM, and provide methodological reference for the research of other chronic disease individualized treatment auxiliary decision system.

The invention belongs to the technical field of artificial intelligence, and relates to a data evaluation method and device, computer equipment and a storage medium, and the method comprises the steps: obtaining health data of a user from a plurality of data sources; preprocessing the health data based on the processing strategy to obtain target health data; performing risk prediction on the target health data based on the risk prediction model to obtain a risk prediction result; performing assessment processing on the risk prediction result based on a knowledge base to obtain a risk assessment result; judging whether the risk assessment result exceeds an early warning threshold value or not; if yes, generating a corresponding intervention measure suggestion based on the risk assessment result; and sending the risk assessment result and the intervention measure suggestion to the user. In addition, the invention also relates to a block chain technology, and the risk assessment result can be stored in a block chain. The risk assessment method and device can be applied to health assessment scenes in the financial science and technology field and the medical field, intelligent risk assessment and early warning are achieved through the risk assessment method and device, and the accuracy and timeliness of risk assessment are effectively improved.

The invention discloses a power transmission line fault edge detection method and system, and relates to the field of power transmission line fault detection, and the system comprises a parameter detection module, a fault preliminary analysis module, an image information collection module, a fault reanalysis module, a comprehensive analysis module, an evaluation processing module, and a database. The working parameters of each power device along the target power transmission line are monitored. And analysis is performed according to the working parameters of the power devices along the target power transmission line to obtain the power coincidence coefficients of the various types of power devices along the target power transmission line, so that the power devices along the target power transmission line are accurately and effectively analyzed, and a data basis is provided for fault detection along the target power transmission line. And the outer protection layer of the target power transmission line is detected and analyzed, and comprehensive analysis is performed by combining the power coincidence coefficients of various types of power equipment along the target power transmission line, so that the accuracy of power transmission line fault detection is further improved.