53 results about "Evaluation treatment" patented technology

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 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 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.

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 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.

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 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.

This invention relates to the field of permanent magnet motor fault diagnosis technology, and more particularly to a deep learning-based method for permanent magnet motor fault diagnosis. The method includes: performing field aggregation and channel mapping processing based on rotor surface temperature values ​​and stator coil temperature values ​​to obtain an operating condition dataset; performing bearing vibration frequency processing, bearing speed processing, and audio signal mapping processing based on the operating condition dataset to generate mechanical screening results; further performing fixed-time-window segmentation, time synchronization, fault tag cross-comparison, and comprehensive evaluation processing on the mechanical screening results to generate a comprehensive evaluation result; and finally, generating alarm signals and maintenance suggestions based on the comprehensive evaluation result to obtain a fault diagnosis result. This invention can streamline the recording relationships within a time window, improving the continuity and verifiability of the fault diagnosis result generation process.

The application relates to a power equipment operation risk assessment method. The method comprises the following steps: in response to a simulation request of a power equipment in a risk scenario, inputting a first control parameter corresponding to the power equipment in the risk scenario into a pre-trained neural physics sandbox model to obtain a multi-physical simulation rendering result; fusing the multi-physical simulation rendering result with an operation environment of the power equipment to obtain a risk preview simulation picture; and performing evaluation processing on the first control parameter based on the risk preview simulation picture to obtain an operation risk assessment result. The method can reduce cost and repeatability.

The invention provides a knowledge base quality detection and evaluation method and system. The method comprises the following steps: inputting real-time learning activity data and real-time environment data into a pre-trained learning effect prediction model, and generating a learning effect prediction value of each operator node in a future preset time period; performing clustering analysis on the learning effect prediction value of each operator node by adopting a knowledge graph self-evaluation processing algorithm based on unsupervised learning to obtain position information of a first cluster center point; according to the position information of the first cluster center point and the position information of a second cluster center point, the coverage degree of a target algorithm is determined, the second cluster center point is a cluster center point included in clustering analysis results generated by other algorithms, and a learning effect prediction model is optimized according to the coverage degree to obtain a prediction result. And adjusting a training strategy of the target post training resource system according to an output result of the optimized learning effect prediction model. According to the technical scheme provided by the invention, the accuracy of learning effect prediction optimization is improved.

The invention belongs to the technical field of artificial intelligence, and relates to a data processing method and device based on artificial intelligence, computer equipment and a storage medium, and the method comprises the steps: receiving a business processing request corresponding to a target client; analyzing the service processing request to extract model identification information; determining a candidate containerization unit corresponding to the model identification information based on the model routing component; screening a target containerization unit from the candidate containerization units based on a load balancing algorithm; preprocessing the customer information of the target customer to obtain feature data; reading model parameters of the target prediction model based on the target containerization unit, and performing evaluation processing on the feature data based on the target prediction model to obtain a data evaluation result; and outputting a data evaluation result. In addition, the invention also relates to a block chain technology, and the data evaluation result can be stored in a block chain. The method can be applied to business data evaluation scenes in the field of financial science and technology, and the processing efficiency of data evaluation is effectively improved.

The invention belongs to the technical field of artificial intelligence, and relates to a task processing method based on a large language model, which comprises the following steps: processing financial corpora based on the large language model to analyze semantic importance information of each network layer in the large language model; generating a specified rank allocation scheme based on the semantic importance information and the parameter budget; training the large language model based on a specified rank allocation scheme to obtain a first large language model; performing fine tuning on the first large language model to obtain a second large language model; if the second large language model does not pass the semantic fidelity verification, adjusting the specified rank allocation scheme to obtain a target rank allocation scheme; performing model training, fine tuning and evaluation processing on the large language model by using a target rank allocation scheme until an iteration termination condition is met, and obtaining a target large language model; and performing task processing based on the target large language model. The method can be applied to task processing scenes in the field of financial science and technology, and the task processing accuracy of the large language model is improved.

The invention discloses a technical performance evaluation method and device for a field support safeguard system. The method comprises the following steps: obtaining a test index set of each subsystem; the test index set comprises test result information of a plurality of test indexes; the test result information is a data sequence; performing data preprocessing on all the test index sets to obtain a preprocessed index set; performing performance evaluation processing on the preprocessing index set to obtain a performance evaluation value set; and performing fusion evaluation processing on the performance evaluation value set to obtain a technical performance evaluation result value of the field support guarantee system.

An evaluation method is performed by an arithmetic circuit and includes obtainment processing (S1), evaluation processing (S2), and presentation processing (S3). The obtainment processing (S1) obtains: image information on a sectional image representing an interested section of an organism including a target section of a testis of the organism generated by use of magnetic resonance of hydrogen atoms; and concentration information on a creatine concentration in the interested section measured by use of magnetic resonance based on chemical exchange saturation transfer. The evaluation processing (S2) generates an evaluation image representing a distribution of evaluation results of a testicular function in the target section based on the concentration information. The presentation processing (S3) presents the sectional image and the evaluation image.

The invention discloses a business environment assessment method, device and equipment, a medium and a product. The method comprises the following steps: when a business environment evaluation request for a plurality of to-be-evaluated areas is received, obtaining original data of each to-be-evaluated area under a plurality of feature dimensions under at least one time slice within a preset duration based on the business environment evaluation request, and determining an original input matrix; performing data fusion processing on the original data in the original input matrix based on a data fusion model to obtain a to-be-fused matrix corresponding to each to-be-evaluated area and a to-be-processed matrix corresponding to a plurality of to-be-fused matrixes; processing the to-be-processed matrix based on a pre-trained business environment evaluation model to obtain an area evaluation result corresponding to each to-be-evaluated area; and based on the region evaluation results corresponding to the plurality of to-be-evaluated regions, determining a business environment evaluation result and feeding back the business environment evaluation result. According to the invention, the business environment evaluation processing of the plurality of to-be-evaluated areas is realized, and the accuracy of the evaluation result is improved.

The application discloses a performance evaluation device and method of a hot food fast food guarantee system, and the method comprises the following steps: collecting historical performance test data sets; the historical performance test data sets comprise test condition data sets and test test data sets; the test condition data sets comprise test condition setting data sequences of each test of the hot food fast food guarantee system; performing estimation processing on the historical performance test data sets to obtain a key test condition information set; collecting test test data sequence sets under test conditions corresponding to the key test condition information set; the test test data sequence sets comprise test test sequences of performance indexes of each type; and performing performance comprehensive evaluation processing on the test test data sequence sets to obtain a comprehensive performance evaluation value of the hot food fast food guarantee system.

This application provides an error-driven self-correcting answer generation method, apparatus, device, and medium, applicable to the financial or medical fields. The method includes: segmenting documents in a target knowledge base to obtain a benchmark dataset; acquiring data to be answered and generating preliminary answer data based on the benchmark dataset and the data to be answered using a RAG model; inputting the benchmark dataset and the preliminary answer data into a preset error assessment model for classification and evaluation to obtain a first target error type and a comprehensive score for a first evaluation index, and determining whether self-correction is needed based on the comprehensive score for the first evaluation index; if self-correction is needed, inputting the benchmark dataset, the preliminary answer data, the first target error type, and the comprehensive score for the first evaluation index into a preset self-correction model to generate a self-correction task; and regenerating the target answer data based on the self-correction task using the RAG model. This allows for self-correction during answer generation, improving system reliability.

The invention provides an embankment flood control risk dynamic weight and threshold collaborative evaluation and disposal method, and belongs to the field of flood control construction. Aiming at the problems that static weight and dynamic hydrological environment are incompatible, basic data are scarce and poor in adaptability, a threshold value is fixed, secondary misjudgment is easily caused, and evaluation and practical operation are disjointed in the prior art, real-time data support is provided by constructing a three-layer data system, and a basic weight and dynamic correction dual-module weighting system is adopted to adapt to environment change, so that real-time evaluation and practical operation are realized. In combination with scene adaptation and a special working condition two-factor threshold calibration system, weight and threshold collaboration is realized, a lightweight architecture of index grouping and parallel computing is established to improve real-time performance, and practical operation guidance is converted through risk level, short plate index and disposal template three-dimensional closed-loop output. According to the method, quantification accuracy, emergency real-time performance and basic feasibility are taken into consideration, the high-risk dike misjudgment rate is reduced, the disposal suggestion landing rate is improved, different types of dikes and complex working conditions are adapted, operability is high, and engineering popularization is facilitated.

The application discloses a kind of multi-modal test data fusion evaluation processing method and device, the method includes: the multi-modal test data set is obtained by acquisition;The multi-modal test data set includes the test numerical information sequence set, test text information sequence set, test picture information sequence set obtained by acquisition in equipment system evaluation process;The multi-modal test data set is preprocessed, and the preprocessed data set is obtained;Using the fusion evaluation model that is trained, the preprocessed data set is processed, and the fusion evaluation result value of equipment system evaluation is obtained.

The invention relates to the technical field of artificial intelligence, and discloses an evaluation processing method and device for a source document generated by retrieval, the evaluation processing method for the source document generated by retrieval comprises the following steps: analyzing the source document to obtain text information, structured information and format information of the source document; based on the text information, the structured information and the format information, performing multi-dimensional evaluation processing to obtain at least two of a structural integrity evaluation result, a content definition evaluation result, a context independence evaluation result and a format normalization evaluation result of the source document; and weighting at least two of the structural integrity evaluation result, the content definition evaluation result, the context independence evaluation result and the format normalization evaluation result to obtain a comprehensive evaluation result of the source document. Through the method, intelligent analysis can be performed on the Word document, and quantitative evaluation is performed on the Word document from multiple dimensions of structure, content and format, so that the document quality is improved.

The invention discloses a geological three-dimensional model source data evaluation method, and relates to the technical field of geological models, and the method comprises the steps: obtaining a drilling data point set and grid system parameters, mapping drilling data points to a grid system, and obtaining a grid coverage statistical result; according to a grid coverage statistical result, calculating transverse and longitudinal distribution indexes, and performing distribution rationality evaluation processing to obtain a source data spatial distribution coefficient; based on the source data space distribution coefficient and the grid system parameters, obtaining a root-mean-square error precision report by calculating the shortest distance from the control point to the surface of the grid system; according to the root-mean-square error precision report and the grid system parameters, whether a blank zone exists in the geologic model or not is checked, a model integrity coefficient is calculated, and a final quality evaluation result is obtained. The invention provides a geological three-dimensional model source data evaluation method, and aims to solve the problem of inaccurate model blank zone detection caused by one-sided distribution evaluation and neglecting of vertical resolution and spatial correlation in the prior art.

This application discloses a method and apparatus for evaluating and processing retrieved presentation documents. The method includes: parsing the presentation document to obtain its text information, visual elements, and structural information, wherein the text information includes presentation text and / or presentation notes; performing multi-dimensional evaluation processing based on the text information, visual elements, and structural information to obtain at least two of the following: a text-image separation evaluation result, a context integrity evaluation result, a structured degree evaluation result, and an information density to noise ratio evaluation result; and weighting at least two of the following: a text-image separation evaluation result, a context integrity evaluation result, a structured degree evaluation result, and an information density to noise ratio evaluation result, to obtain a comprehensive evaluation result for the presentation document.

The application provides a kind of enterprise evaluation processing method, device and server, it is related to natural language processing technical field.The enterprise evaluation processing method uses the information entropy of text feature vector, the similarity of text feature vector and the cluster center of the set of text feature vector to which it belongs, the difference of text feature vector and other text feature vectors in the set of text feature vector, determine the value of the text feature vector of each group of enterprises, and select the classification model trained by the text feature vector of the value ranking top N, to accurately determine the category of the enterprise to be evaluated.So, the reliability of the evaluation result of subsequent evaluation processing according to the category of the enterprise is also high.

The invention relates to the technical field of artificial intelligence, and provides a digital weight reduction method, device and equipment and a medium, which are applied to the fields of medical treatment, finance and the like, and the method comprises the following steps: analyzing multi-modal data of a user to obtain analysis data; fusing the analyzed data to obtain a fused data set; evaluating the fused data set by using an evaluation strategy to obtain an evaluation report; generating the evaluation report based on the generation strategy to obtain an intervention scheme; and performing weight reduction intervention on the user based on the intervention scheme. By implementing the embodiment of the invention, the multi-modal data is analyzed and fused to obtain the fused data set, the evaluation strategy is utilized to evaluate the fused data set to obtain the evaluation report, and the evaluation report is generated based on the generation strategy to obtain the intervention scheme, so that weight reduction intervention is performed on the user based on the intervention scheme, and the user experience is improved. The relevance of the data is ensured to support the generation of a personalized and dynamic scientific weight reduction scheme, so that the processing efficiency is improved.

According to the extracorporeal shock wave early intervention scheme evaluation method and system provided by the invention, each intervention scheme is obtained based on the corresponding rehabilitation condition and the professional treatment scheme of the target object, and the rehabilitation condition data set is utilized to debug the treatment effect evaluation network to obtain the treatment effect evaluation network. An early intervention scheme set is evaluated through the treatment effect evaluation network, an early intervention scheme evaluation result is obtained, the early intervention scheme set is generated based on the rehabilitation condition data set, and the question and answer network is used for processing question and answer tasks of the target object. It can be seen that the to-be-treated effect evaluation network is debugged through the shock wave intervention data of the target object and the professional treatment scheme, and intervention popularity training is performed through the rehabilitation condition data set on this basis, so that the evaluation accuracy of the question-answer network in the treatment effect of the personalized patient corresponding to the shock wave intervention data can be improved.

The application belongs to the technical field of artificial intelligence, and relates to a data evaluation method and device based on artificial intelligence, a computer device and a medium, which comprises the following steps: collecting target data of a user from a plurality of preset dimensions; performing feature construction processing on the target data to obtain corresponding multi-dimensional feature data; performing standardization and fusion processing on the multi-dimensional feature data to obtain corresponding fusion features; performing feature mapping processing on the fusion features based on a preset data evaluation model to obtain a potential risk embedding representation corresponding to the fusion features; performing score mapping processing on the potential risk embedding representation based on a preset scoring strategy to obtain corresponding score data; performing risk evaluation processing on the user based on the score data to obtain a corresponding risk evaluation result; and outputting the risk evaluation result. The application can be applied to a data risk evaluation scene in the field of financial technology, can realize dynamic evaluation processing on credit risks of a user, and improves the accuracy of risk evaluation.