16 results about "Evaluation treatment" patented technology

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.

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.

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.

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.

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.

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 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.

The present disclosure relates to the technical field of text processing, and provides a text question and answer method and device, electronic equipment and readable storage medium. The method comprises: performing tool search processing on a question text based on a preset tool library to obtain a candidate tool list; performing conditional filtering processing on the candidate tool list to obtain an updated tool list; performing adaptation degree evaluation processing on the updated tool list based on a preset adaptation degree threshold to obtain an evaluation tool list; performing capacity verification processing on the evaluation tool list to obtain a target tool list; and performing retrieval enhancement generation processing on the target tool list and the question text to obtain a target answer text corresponding to the question text. The real-time adaptability of the tool set and the dynamic dialogue context is enhanced, the task execution efficiency and the answer accuracy in the multi-round dialogue scene are improved, the stability and reliability of the operation are ensured, the flexibility of tool calling is improved, the task execution efficiency is improved, and the coherence of the text dialogue is enhanced.

This application discloses a data evaluation method, apparatus, electronic device, and storage medium. The method includes: acquiring data to be evaluated associated with a target object; converting the data to be evaluated into structured data corresponding to the target object, wherein the structured data includes at least one field and field values ​​corresponding to the fields; searching a preset rule base based on the structured data corresponding to the target object to determine a set of rule items matching the target object; performing evaluation processing on at least one dimension based on the structured data and the set of rule items to determine at least one evaluation result for the target object; and generating an evaluation report for the target object according to a preset evaluation report template based on the at least one evaluation result for the target object. Therefore, an evaluation report for the target object can be generated based on the data to be evaluated associated with the target object, improving the efficiency and accuracy of data evaluation.

The present invention relates to a trace-aware evaluation system and method implemented as a dedicated computational system for monitoring and assessing the operational behavior of long-running artificial intelligence agents. The system is configured to continuously receive execution records generated during agent operation and to assign temporal identifiers to the records for maintaining chronological continuity. The system stores the execution records along with contextual descriptors representing agent state transitions, interaction histories, and task conditions, and organizes the stored information into structured trace segments corresponding to reasoning cycles and action sequences. A correlation processor analyzes relationships among the trace segments across different time intervals to determine continuity of reasoning, context utilization patterns, and decision dependencies. An evaluation processor generates performance indicators reflecting behavioral consistency, trace coherence, stability of decision patterns, anomaly occurrence, and long-term operational reliability.

This application relates to the field of data processing technology, and discloses a planning and evaluation system, computer equipment, and storage medium for traditional Chinese medicine (TCM) diagnosis and treatment. The system includes: a data acquisition module for acquiring multimodal monitoring data of the target subject during the current treatment phase; an effect prediction module for performing effect simulation and prediction based on the multimodal monitoring data and the target subject's current intervention plan to obtain adjustment results; and a feedback evaluation module for simulating and evaluating the current intervention plan based on the adjustment results to obtain feedback evaluation results. The feedback evaluation results provide quantitative references for treatment adjustments to the decision-making end, enabling the generation of subsequent intervention plans for the target subject in the next treatment phase. These three modules work together to constitute a planning and evaluation system for TCM diagnosis and treatment, providing physicians with real-time decision support and significantly improving the accuracy and adaptability of subsequent intervention plans.

The application discloses a transverse cerebellum section quality evaluation and biological measurement method and system, and belongs to the technical field of medical image analysis and processing. The method comprises the following steps: acquiring a transverse cerebellum section sample in a fetal ultrasound image, performing data preprocessing, constructing a target detection and semantic segmentation dataset, training a target detection and semantic segmentation network as a prediction model, and building a corresponding quality evaluation system and biological index post-processing system according to the output result of the prediction model. The prediction model and the evaluation processing system are effectively combined together to realize end-to-end evaluation and measurement of the transverse cerebellum section ultrasound image. The application combines the section quality evaluation and the biological index measurement on the transverse cerebellum section for the first time, establishes a scientific and objective quantitative evaluation system and a fast and accurate biological index measurement method, and facilitates the judgment of the section quality by doctors.