13 results about "Process evaluation" patented technology

The application discloses a kind of based on multi-source data fusion and process evaluation's college student comprehensive performance automatic generation method and system, including S1 establishes ideological and political evaluation model, academic performance evaluation model, practical ability evaluation model, comprehensive quality evaluation model, development potential evaluation model comment model. S2 by middleware establishes standardization interface and automatically reads the heterogeneous data source data of educational administration system, school system, campus card system, library system, scientific research and teaching research practical training system, second classroom activity platform etc.S3 to behavior sequence is carried out pattern recognition and feature extraction, establishes student panoramic data warehouse, and the data of step S2 is labeled with S1 evaluation model label and storage.S4 user selects comment purpose.S5 dynamic weight distribution.S6 to student data is screened.S7 comment automatic generation.S8 artificial check comment.S9 generation visual report.The application improves work efficiency, and can provide accurate student performance in school for parents and employing units.

The present application relates to the technical field of medical instrument disinfection, in particular to a medical instrument cleaning and disinfection process evaluation system, which comprises an instrument entrance identification module, a material bacteria spectrum adaptation module, a use disinfection path reconstruction module, a combined instrument standard comparison module and a disinfection intensity fitting verification module.In the present application, the state of the instrument entering the process is accurately identified through synchronous verification of the instrument binding code, serial number and response timing, and the matching rules between the heat conductivity, texture grade and bacteria toxicity are combined to determine the objects that cannot be directly disinfected.Based on the historical use trajectory and the deviation score, a disinfection mode set is dynamically constructed, the consistent mode number in the combined processing is selected through the intersection comparison between the mode conditions, and the mode parameters and instrument requirement values are further compared as needed to realize the full-process adaptation and verification of the path selection, mode condition and processing intensity, and to enhance the matching rationality and execution consistency in the multi-instrument processing process.

The application discloses a tunnel construction whole-process evaluation method, system and equipment under a sensor network, relates to the technical field of geotechnical engineering structure health monitoring, and comprises the following steps: multiple types of sensors are arranged at each stage of tunnel construction and operation; multiple-source monitoring data streams of settlement, temperature, soil pressure and stress and strain are collected; after denoising, space-time alignment and fusion processing, a multi-dimensional data set is constructed in combination with geological construction and material data; a special dynamic evaluation model is established in stages; the safety state of the structure is quantitatively evaluated; and real-time early warning of an abnormal state is completed according to the evaluation result. The application solves the technical problems that the whole-life-cycle segmented evaluation is fragmented, the multiple-source monitoring data is chaotic, the hidden risk identification is lagging, and the safety state cannot be dynamically quantified in the safety control of tunnel construction, achieves dynamic control of the safety state of the whole process of tunnel construction, early warning of potential hidden dangers, and provides a reliable basis for construction risk prevention and control.

The application provides a kind of intelligent scheduling method and system based on data layering, it is related to intelligent workshop scheduling technical field. Specifically includes: integrating workshop multi-source production data, constructing digital twin layer, constructing workshop digital twin model for whole workshop data, further dividing high-frequency update equipment model according to the frequency of equipment data update;According to the difference of data frequency, the digital twin model is dynamically updated in layers;Based on model output, collaborative realization equipment maintenance and production scheduling, process evaluation and iterative optimization of digital twin model are carried out.The application integrates multi-source production data, implements hierarchical dynamic scheduling combined with data frequency difference, avoids full model redundant operation, improves scheduling response efficiency, reduces equipment downtime, achieves the intelligent whole-process collaborative scheduling goal of significantly improving workshop task completion efficiency and equipment utilization.

The application discloses a water conservation coal mining process evaluation and screening method suitable for Jurassic coalfield, and belongs to the technical field of coal mining. The method solves the problems that the existing evaluation method cannot fully combine the geological characteristics of the Jurassic coalfield, the index weight determination is not scientific enough, and the optimization result lacks robustness test. The main points of the method are to construct a three-dimensional index system including water conservation effect, economic benefit and engineering feasibility, and to include indexes such as separation layer development time sequence matching degree which are aimed at the Jurassic coalfield; after collecting the original data of the selected process, the objective weight is calculated by using the entropy weight method, the coefficient of variation method and the CRITIC method, and then the geometric mean method is used to combine the most weight; the data is processed by dimensionless, the linear weighted comprehensive method is used to calculate the comprehensive evaluation value and sort the optimal process, and finally the robustness of the optimization result is verified through the sensitivity analysis. The method is mainly used for providing basis for scientifically selecting and evaluating the water conservation coal mining process of the Jurassic coalfield mine.

The application relates to the technical field of spacecraft assembly, and provides a spacecraft assembly process generation method based on multi-model cooperation. The method comprises the following steps: receiving a current process generation task prompt instruction, analyzing and content extracting a target spacecraft design file and a process flow framework template file provided, so as to generate a first edition process flow of the target spacecraft; generating an assembly process sequence of the target spacecraft by using a process generation model; generating a second edition process flow and a third edition process flow by using two pairs of generation models and a check model; and performing process evaluation on the third edition process flow. The application reduces the excessive dependence of process flow design and checking on manpower, reduces the probability of human error, improves process compilation efficiency, and realizes the automation of the spacecraft assembly process flow.

The application provides a cooperation argumentation state representation method and system based on an online scientific argumentation map. Through the automatic and structured analysis and calculation of the interactive text and behavior data of online cooperation argumentation by an educational large language model, a paradigm shift from "post-event manual evaluation" to "process intelligent diagnosis" is realized. The system can quantitatively represent the multi-dimensional state of learners in cooperation depth (such as participation and interaction) and argumentation quality (such as logical mode and knowledge application) in real time and dynamically, and synchronously generate a visual scientific argumentation map integrating individual and group perspectives. This not only greatly improves the objectivity, timeliness and precision of process evaluation, enabling teachers to accurately grasp the learning situation and intervene in time, but also provides learners with intuitive and concrete reflection scaffolds, thereby effectively promoting the development of their high-order thinking and scientific argumentation literacy.

This invention relates to the field of labor education evaluation technology, specifically disclosing a system and method for evaluating the effectiveness of labor education practices. The system includes a data acquisition module, a blockchain evidence storage module, an AI behavior analysis module, a closed-loop control module, and a central database. The data acquisition module collects multi-source data, including IoT check-in data, videos, multi-subject evaluations, and results. The blockchain evidence storage module encrypts and distributes the data using the SHA-256 algorithm. The AI ​​behavior analysis module uses the YOLOv8 model to identify labor behaviors and quantify parameters. The closed-loop control module generates evaluation results and outputs task adjustment and teaching optimization instructions, forming a periodic closed loop. This invention solves the problems of difficulty in ensuring the authenticity of existing labor education evaluation data, lack of process evaluation, and disconnect between evaluation and teaching, achieving full-chain traceability of evaluation, intelligent analysis, and integrated teaching.

This invention relates to the field of intelligent manufacturing technology and discloses an intelligent manufacturing quality inspection method and system based on artificial intelligence, including: S1, performing quality inspection on continuously produced products; S2, generating a single-piece quality state to characterize the quality features of the individual product; S3, organizing multiple single-piece quality states according to manufacturing sequence information or time information; S4, constraining the continuity of the single-piece quality states in the time dimension; S5, based on a multi-level quality state expression structure; and S6, outputting the process quality state. By constructing a multi-level quality state expression structure containing a single-piece quality state layer and a process quality state layer, and introducing a process evaluation constraint mechanism based on time continuity in the process quality state construction and judgment process, the manufacturing process quality inspection is expanded from discrete single-piece judgment to overall quality state judgment of a continuous production process, thereby improving the ability to characterize quality changes in the manufacturing process.

This invention discloses a method and system for speech recognition and student process evaluation based on dynamic vocabulary injection, relating to the fields of artificial intelligence and smart education technology. This invention aims to solve the problem of low recognition rate of homophones in existing speech recognition technologies, leading to inaccurate attribution of process evaluation results and high manual recording costs. The method includes: obtaining a student list for the target teaching scenario; pre-injecting the list as a dynamic vocabulary into an ASR (Automatic Speech Recognition) engine for decoding weight bias; acquiring real-time teaching speech streams, using the ASR engine with injected dynamic vocabulary for accurate recognition, and outputting text containing specific student names; using a Natural Language Processing (NLP) model to extract entities from the text, separating name entities and performance evaluation entities; finally, inputting the performance evaluation entities into an AI scoring model to automatically generate a quantitative score and include it in the student's process evaluation file. This invention completely solves the problem of recognizing homophones and proper nouns, realizing an accompanying, seamless, automated evaluation scoring closed loop, greatly reducing the recording burden on teachers.

The application relates to an online evaluation method for breaking characteristics integrated in a smart circuit breaker and relates to the technical field of online monitoring control. Data is collected through an internal breaking parameter collection system; a four-dimensional feature vector is extracted from the collected data, and is mapped to a unified time axis after wavelet threshold denoising; a hybrid evaluation model combining fuzzy logic and LSTM is constructed, the feature vector is divided into small, medium and large fuzzy categories in the fuzzy logic layer, the LSTM layer outputs a quantitative evaluation value, and the evaluation threshold is dynamically corrected based on the service life and breaking times of the circuit breaker; the processed feature vector is input, the hybrid evaluation model outputs an evaluation result, and a residual life prediction value is calculated according to an exponential decay model; when the evaluation result is substandard, a deviation value is calculated in combination with real-time power load data, and an adjustment recommendation scheme is generated. Through the whole-process evaluation of evaluation, prediction, optimization and verification, the application realizes high adaptability and reliability in a complex power environment, and has wide application value.

This invention belongs to the field of power system analysis technology, and discloses a method, system, equipment, and medium for evaluating the strength support performance of a superconducting synchronous condenser (SSC). The method includes: acquiring power grid operating parameters and the physical parameters of the connected SSC; calculating the static short-circuit ratio, reflecting the intrinsic strength of the power grid, based on the power grid operating parameters; constructing a dynamic equivalent factor based on the physical parameters of the SSC; and coupling the static short-circuit ratio and the dynamic equivalent factor to construct a dynamic full-process evaluation index that comprehensively reflects the SSC's strength support effect on the power grid system. By introducing a dynamic equivalent factor to correct traditional indicators, a leap from static grid strength to the dynamic support capability of equipment is achieved. Furthermore, a comprehensive dynamic full-process evaluation index, reflecting the SSC's strength support effect on the system throughout the entire fault process, is constructed based on the dynamic equivalent factor, solving the technical problem that traditional indicators cannot accurately quantify the instantaneous dynamic support mechanism.