67 results about "Expert evaluation" patented technology

The invention relates to the field of data processing, and provides a software cost method and system based on dynamic configuration and hierarchical analysis. The method comprises the following steps: dynamically loading corresponding configuration parameters and algorithms by evaluating a method identification field; constructing a standardized cost parameter configuration system, including configuring an estimated function point reference value, an estimated function point weight coefficient and a scale adjustment factor; based on the evaluation method, a tree budget configuration table is preset, hierarchical node design is adopted, a budget tree is constructed, and a tree budget configuration and cost declaration / evaluation header is formed; transferring the configuration right of the tree budget configuration and the cost declaration / evaluation header to the back end, so that the back end dynamically loads a preset header template according to the enabled cost standard, and synchronously injects field attribute rules and calculation formula metadata; obtaining an unstructured document uploaded by a user, and analyzing the unstructured document and the header template by adopting a large language model to obtain software cost details; and generating an evaluation report through the expert review software cost details.

The embodiment of the invention provides a medicine evaluation method and related equipment, and belongs to the technical field of information processing. The method comprises the following steps: acquiring medicine input information corresponding to a first medicine; the first medicine is any medicine, and the medicine input information comprises medicine type data; generating a corresponding medicine evaluation template according to medicine type data in the medicine input information; collecting expert evaluation information corresponding to the first drug through the drug evaluation template; the expert evaluation information comprises text data and score data; and performing text analysis on the text data corresponding to the first drug through the drug evaluation model to generate a model evaluation score, and integrating the model evaluation score and the score data to obtain a target evaluation result corresponding to the first drug. According to the embodiment of the invention, the consistency and objectivity of the drug evaluation result can be remarkably improved, so that more comprehensive and intelligent decision support is provided for drug selection of medical institutions.

The invention discloses an expert review componentization system and a review method, belongs to the technical field of software systems, and aims to solve the technical problems of poor universality, insufficient intelligence and rigid process in the process of business declaration and qualification affirmation. Comprises: a component library configuration module for constructing a standardized review component and constructing a component library based on the review component; the expert database configuration module is used for collecting review experts to construct an expert database according to the review requirements of each business scene; the review rule configuration module is used for pulling related review components from the component library according to review rules and constructing a review process based on the pulled review components; the expert extraction module is used for pulling related reviews from an expert database to construct a review expert group and setting expert review rules; the review analysis module executes a review task based on a review process, and summarizes review suggestions of review experts to form a review result; and the data storage module is used for storing the review rule, the review expert group and the review result.

This invention discloses a method and system for application design transformation based on technological experience, relating to the field of digital technology. The method includes: collecting open-source technology product data via the internet to construct a digital technology experience center; providing online technology experiences for students to obtain experience monitoring data; designing online courses based on a technology application creation platform to obtain online teaching courses; teaching students to obtain technology application concept design proposals; conducting simulation verification and evaluation through a mechanism simulation system to obtain simulation evaluation results for the design proposals; presenting the technology application concept design proposals in a roadshow to obtain a design demonstration dataset; conducting online expert evaluation; and transforming the technology application concept design proposals into innovative achievements based on the evaluation results. This addresses the technical problems of limited teaching resources, limited practical scenarios, and restricted technological innovation capabilities in existing science and technology education, achieving the technical effect of enriching technological experiences and enhancing technological innovation capabilities.

The present application relates to expert feedback driven government procurement intelligent auxiliary bid evaluation system, including: tender document analysis module; bid document processing module; expert evaluation annotation module; and evaluation model and its optimization module; data intercommunication between tender document analysis module, bid document processing module, expert evaluation annotation module, evaluation model and its optimization module. The feedback mechanism of expert evaluation is emphasized, the close contact between expert experience and model optimization is further strengthened, the expert experience is effectively converted into model optimization power, the optimization process of the model is accelerated, the system can reach a high evaluation level in a relatively short time, and can continuously maintain the industry forefront, better meet the growing demand of government procurement business, help the procurement party to select better and more suitable suppliers, and realize efficient allocation of resources.

This invention provides an improved FMEA device that considers the relationship between uncertainty and failure modes. It features the following components: an SVTraNN scoring conversion module for obtaining the SVTraNN evaluation matrix; an expert weight calculation module for calculating expert weights; an expert evaluation summarization module for calculating the SVTraNN decision matrix; a subjective weight calculation module for calculating the final subjective weight of each risk factor; an objective weight calculation module for calculating the objective weight of each risk factor; a comprehensive weight calculation module for calculating the comprehensive weight of each risk factor; a comprehensive score calculation module for calculating the comprehensive score of each risk mode; a risk ranking module for obtaining the risk ranking result of each risk mode; and a risk level module for obtaining the risk level of each risk mode. In summary, this method can effectively assess the risk level of risk modes.

The invention discloses a leg posture analysis and rating system for a football player in a ball kicking process, and the system comprises a data collection unit which collects four-stage kinematics parameters of kicking, kicking and stretching, backward swinging, forward swinging and ball touching through a three-dimensional motion capture system and a high-speed camera; the data processing unit is used for processing parameters and extracting characteristic parameters of each stage; the expert evaluation interface is used for receiving evaluation data of multiple experts on different ball kicking technology types on the multi-score influence factors; the weight calculation unit is used for calculating an influence factor attribute weight by using a Bayesian method based on expert data; the rating decision matrix construction unit is used for constructing a comprehensive matrix in combination with a weight rough projection method; the multi-angle analysis unit is used for performing multi-angle risk rating by fusing a rough set theory and an approximate ideal solution sorting method; and the result output unit is used for outputting the posture quality grade and the training suggestion. According to the method, the actual requirements of football training on precision, standardization and comprehensiveness of posture analysis can be met.

The present application relates to the technical field of traditional Chinese medicine preparation, and particularly relates to a method and system for optimizing a frying process of traditional Chinese medicine decoction pieces. Formula information and process requirements of target traditional Chinese medicine decoction pieces are obtained; a frying process scheme of similar traditional Chinese medicine decoction pieces is retrieved from a traditional Chinese medicine frying expert knowledge base; initial parameters are generated by fusing the frying process scheme; first-round frying is performed; process data are collected by a multi-modal sensor; adjustment suggestions are proposed by experts; parameter adjustment schemes are generated in combination with the expert suggestions and the process data; interactive optimization is performed for multiple rounds; and optimal frying process parameters are recorded and stored in the knowledge base. By constructing a formula information-driven knowledge retrieval mechanism, a multi-modal sensing monitoring system, a parameter adjustment strategy combining expert evaluation and data analysis, and an interactive iterative optimization framework, a closed-loop optimization system is formed, and technical problems such as difficulty in knowledge reuse, single process monitoring, lack of systematic support for parameter adjustment, and insufficient human-machine cooperation in traditional Chinese medicine frying processes are solved.

The invention discloses an evaluation analysis method and system for review behaviors of scientific research project review experts. The evaluation analysis method and system cover data acquisition and grouping modeling, professional level and professional ability baseline determination, technology and management review ability evaluation, credit and review attitude evaluation, comprehensive score generation and output and the like. According to the method, the evaluation result distribution of the evaluated evaluation expert in different evaluation groups and the evaluation result deviation condition of the evaluated evaluation expert in the same evaluation group are comprehensively investigated, the score distribution degree and the score deviation degree are adopted as two core indexes, and the technical evaluation ability and the management evaluation ability of the evaluation expert are evaluated. On the basis, three first-level evaluation indexes including professional ability, credit evaluation and review attitude are adopted, and objective quantitative evaluation is carried out on the evaluated experts. The invention provides an objective and scientific evaluation expert evaluation method, also has the characteristic of convenient and efficient calculation, and is suitable for large-batch scientific research project evaluation expert evaluation management.

The invention provides a hydroelectric power transmission project construction accident risk analysis method based on an RF-WA-PHFWFGSM operator, and the method comprises six core steps: data preprocessing, RF preliminary feature screening, improved expert simulation evaluation, WA-PHFWFGSM operator aggregation, comprehensive verification, and result output, and each step is progressive layer by layer to form a complete risk analysis closed loop of data, features, evaluation, verification, and application. Aiming at the problems of expert evaluation hesitation and information uncertainty, a probability hesitation fuzzy set (PHFS) is used for processing qualitative attribute feature evaluation, expert hesitation attitudes and fuzzy information are completely reserved through language terms and probability distribution and quantification of expert opinions, information loss caused by the fact that a traditional method is simplified into a determined numerical value is effectively avoided, and the method has the advantages of being high in accuracy and high in reliability. And the authenticity and integrity of expert evaluation results are improved.

The present application relates to a multi-modal data inconsistency detection and cleaning method and system based on adaptive energy guidance, belonging to the field of artificial intelligence and data mining technology. The present application proposes a multi-modal data inconsistency detection method based on adaptive energy guidance. First, a multi-expert uncertainty estimation framework is constructed to effectively mine multi-dimensional modal semantic correlation information such as prediction uncertainty, cross-modal consistency and teacher-student difference. Second, according to the multi-expert evaluation signal, an adaptive energy scoring mechanism is designed to effectively aggregate and quantify the sample modal consistency by constructing a comprehensive energy function and a weighted function based on Boltzmann distribution. Finally, a dynamic data cleaning and screening strategy based on energy score is constructed to improve the quality of the data set and the robustness of the downstream model, and better achieve the purpose of data service.

The invention discloses an old-age care case matching method based on big data processing, and the method comprises the following steps: collecting and integrating the care case data of the elder of a nursing home, and constructing a multi-dimensional information set; performing standardized field mapping and time serialization processing on the data, and unifying the data into a structured data set; performing text analysis based on the medical subject word bank to generate a searchable semantic tag set; inputting the structured data set and the semantic tag set into a TabTransform network based on an attention mechanism, extracting interaction features between fields, and generating a fusion feature vector; similarity retrieval is achieved through FAISS, and a similarity ranking candidate case set is output; and in combination with the nursing effect and expert evaluation, dynamically marking high-quality cases to form reusable nursing scheme resources. According to the invention, rapid matching of nursing cases and intelligent recommendation of high-quality schemes can be realized.

The application provides a non-intrusive experimental evaluation system and method for pilot human-machine trust behavior, and relates to the technical field of human-computer interaction, which comprises the following steps: collecting a plurality of original data points including eye movement trajectory data points, operation instruction data points and flight instrument parameter data points of a pilot to form an objective behavior data set; receiving a plurality of subjective evaluation data points of the pilot based on the objective behavior data set to form a subjective evaluation data set; receiving a plurality of expert evaluation data points of a flight expert according to the subjective evaluation data set and the objective behavior data set to form an expert evaluation data set; and synchronously matching each data point in the objective behavior data set, the subjective evaluation data set and the expert evaluation data set according to a flight task time node to generate a multi-dimensional behavior mapping data set with time corresponding relationship. The application can realize accurate identification, dynamic evaluation and quantitative analysis of pilot human-machine trust behavior.

The application discloses a medical service process iterative decision method and system based on multi-source feedback information, and the method steps comprise the following steps: in step S01, multi-source feedback information of each link of a medical service process is acquired, and service satisfaction scores and service quality scores are obtained; in step S02, the medical service process is modeled as a dynamic Bayesian network model, an emotion value after state transition is calculated by using an emotion transmission function, and a quantitative transmission effect is obtained by using an emotion transmission coefficient, and a time sequence cascade model is trained; in step S03, according to the deviation between expert evaluation benchmark data and the satisfaction scores, the feedback information weight is adjusted; in step S04, a multi-objective optimization function is iteratively solved, and in the solving process, the time sequence cascade model is used to predict the satisfaction change under different medical service processes, and an optimal medical service process scheme is obtained. The application can optimize the service efficiency and resource utilization rate of medical services, and improve the medical experience of patients.

A supply chain risk identification method, system, device and medium belong to the technical field of supply chain risk management. The risk identification method comprises: acquiring characteristic information of a supply chain risk event, the characteristic information of the supply chain risk event comprising event fuzzy description and corresponding parameter information; the parameter information comprising expert evaluation data and supply chain platform operation data; inputting the event fuzzy description into a supply chain language large model for matching processing, and outputting a plurality of risk index items corresponding to the event fuzzy description, the risk index items comprising events affecting supply chain capacity or transportation; and determining the risk levels of the plurality of risk index items corresponding to the parameter information. The risk identification method can improve the supply chain risk identification capability, make it possible to comprehensively perceive multi-source heterogeneous risk factors in the whole chain range and early warn key node risks, and realize dynamic monitoring and accurate identification of complex equipment supply chain operation risks.

This invention discloses a digital evaluation method for the sensory quality of formulated products, comprising: establishing a training sample matrix X using measurement data of m formulated products as training samples; establishing an expert sensory evaluation vector Y by combining expert evaluation results of the training samples; and setting the test samples x... m+1 Add the training sample matrix X to form set X (m+1) The number of sensory indicators in the expert sensory evaluation vector Y is used as the number of test samples x. m+1 Assign the same number of sensory indicators; based on set X (m+1) The distance between samples is used to express the distributional differences between samples using a similarity metric. Based on the distributional differences between the test sample and the training sample, the sensory index evaluation value of the training sample with the highest distributional similarity is selected to predict the test sample x. m+1 The sensory quality assessment method of this invention is simple and effective, and the assessment results are not affected by subjective human factors, thus having high reliability.

The invention discloses a medical service process iterative decision-making method and system based on multi-source feedback information, and the method comprises the steps: S01, obtaining the multi-source feedback information of each link of a medical service process, and obtaining a service satisfaction score and a service quality score; s02, modeling the medical service process into a dynamic Bayesian network model, calculating an emotion value after state transition by using an emotion transfer function, quantifying a transfer effect through an emotion transfer coefficient, and training to obtain a time sequence cascade model; s03, adjusting the feedback information weight according to the deviation between the expert evaluation reference data and the satisfaction score; and step S04, performing iterative solution on the multi-objective optimization function, and predicting satisfaction variation under different medical service processes by using a time sequence cascade model in the solution process to obtain an optimal medical service process scheme. The service efficiency and the resource utilization rate of medical services can be optimized, and the medical experience of patients is improved.

The invention relates to the field of electric energy quality evaluation, and particularly discloses an electric energy quality evaluation method and system. The method comprises the steps of obtaining a plurality of evaluation parameters based on collected electric energy data, and constructing an evaluation parameter matrix based on the evaluation parameters; based on the plurality of evaluation parameters, obtaining a correlation parameter matrix through correlation analysis; performing orthogonal rotation operation on the related parameter matrix to obtain a final related parameter matrix; and obtaining a coefficient matrix based on the final related parameter matrix, continuously multiplying the coefficient matrix by the evaluation parameter matrix and the expert evaluation matrix to obtain an evaluation result matrix, and calculating a modulus of the evaluation result matrix to obtain an evaluation value of the power quality. According to the method, the evaluation parameters are obtained by processing the electric energy initial data, correlation analysis is carried out on the evaluation parameters, related data with large influence are reserved, and dispute caused by manual screening is avoided. Meanwhile, assessment experience of experts is introduced into assessment data processing, so that assessment of the system is more objective and has reference value.

The invention discloses a crude oil storage tank health state grading evaluation method and a related device, and relates to the technical field of crude oil storage tank health state evaluation, and the method comprises the steps: carrying out the grading evaluation of the health state of a crude oil storage tank based on storage tank basic data, real-time monitoring and detection data and previous inspection and maintenance data of the crude oil storage tank; determining the health degree of each secondary evaluation index in each primary evaluation index in each of the plurality of factors, determining the subjective weight of each secondary evaluation index based on expert evaluation data of the crude oil storage tank, and determining the subjective weight of each secondary evaluation index based on historical detection data of each secondary evaluation index. And determining the objective weight of each secondary evaluation index, fusing the subjective weight and the objective weight, determining the fusion weight of each secondary evaluation index, performing comprehensive evaluation based on the health degree of each secondary evaluation index and the fusion weight, and determining the health state of the crude oil storage tank. According to the invention, the scientificity and accuracy of crude oil storage tank health state evaluation can be improved.

The invention discloses a multi-modal data-based user cooperation and interaction capability evaluation method, system and terminal, and the method comprises the steps: designing a team task under a pressure situation, selecting a plurality of users to participate in the team task, and obtaining the multi-modal data of the plurality of users in the team task; performing feature extraction on the multi-modal data to obtain a multi-modal intermediate variable, and inputting the multi-modal intermediate variable into a trained multi-modal intermediate variable analysis model for feature extraction to obtain a current multi-modal feature; and inputting the current multi-modal features into a trained multi-modal fusion and evaluation model to carry out multi-feature fusion and evaluation to obtain respective cooperation and interaction capability evaluation results of the plurality of users. According to the method, an automatic evaluation framework with two-stage verification is constructed, and the accuracy and reliability of user cooperation and interaction ability evaluation are greatly improved through a training and verification mechanism with double introduction of expert evaluation conclusions and psychological measurement data.

The application discloses a substation communication network fragile structure evaluation method based on a complex network theory, which comprises the following steps: constructing a substation communication network model, generating link weights based on attack paths of the substation communication network model, combining the complex network theory with the link weights, and calculating a plurality of node vulnerability values; based on the node vulnerability values, comprehensively considering local information and global information of the links, and calculating a plurality of link vulnerability values; and based on the node vulnerability values and the link vulnerability values, respectively evaluating the fragile structure of the substation communication network. The application can solve the problems of fast network attack updating speed and difficulty in quantification and subjectivity of expert evaluation in the prior art.

The application provides a kind of intelligent manufacturing capability maturity evaluation method, device and equipment, the method comprises: the intelligent manufacturing capability maturity evaluation index system of multiple different dimensions covering target enterprise is constructed;Obtain the evaluation information set of the evaluation expert set to target enterprise;Based on evaluation information set, construct probability language decision matrix framework;Based on BWM algorithm, evaluation information set is handled, to obtain the weight of different evaluation attributes involved in probability language decision matrix framework, form probability language decision matrix based on weight and probability language decision matrix framework;Based on VIKOR algorithm, probability language terms in probability language decision matrix are handled, and the intelligent manufacturing capability maturity level evaluation result of target enterprise is obtained.The method of the application can objectively and accurately collect expert evaluation information to evaluate the intelligent manufacturing capability maturity of enterprise.

The application provides a method and device for determining jaw facial symmetry based on a three-dimensional image. The method comprises the following steps: in response to a request instruction input by a user, acquiring a three-dimensional image of the jaw face of the user and complaint information input by the user; identifying position information of a plurality of preset landmark points in an image region; determining second scoring information of the image region according to the position information of the preset landmark points; if the request instruction indicates that the user currently does not need expert evaluation services, determining asymmetry result information of a part corresponding to the image region according to the complaint information and the second scoring information; and pushing the asymmetry result information to the user. The application divides the three-dimensional image of the jaw face into image regions, so as to obtain asymmetry result information of each image region in the jaw face, and makes the asymmetry result more comprehensive. Furthermore, the asymmetry result can be determined in combination with the information and the second scoring information, so as to improve the accuracy of the asymmetry result evaluation.

The invention provides an unmanned aerial vehicle take-off and landing point design method and system based on an urban CIM model, relates to the field of low-altitude traffic planning, and solves the technical problems of insufficient site selection scientificity and low efficiency due to the fact that unmanned aerial vehicle take-off and landing point selection depends on artificial experience in the prior art. The method comprises the following steps: determining a primary selection point location according to acquired CIM data, extracting a quantitative index of the primary selection point location, calculating the fitness, and screening out a first alternative point location; the demand intensity is calculated based on the demand urgency degree and demand quantity of each unit for the unmanned aerial vehicle, the feature vector of the first alternative point location is constructed in combination with the fitness, a comprehensive score is determined through standardization processing and principal component analysis, and a second alternative point location is screened out; optimizing the second alternative point location by using a clustering algorithm to obtain a third alternative point location; environment correction and expert evaluation verification are conducted on the third alternative point locations, final scores are calculated, and the optimal point locations are obtained through screening in combination with the needed number. The method is used in the planning and designing process of the unmanned aerial vehicle take-off and landing points in the urban range.

The embodiment of the present application relates to a kind of processing method and device for brain efficiency prediction based on multidimensional index, the method comprises: the multidimensional index set corresponding to multidimensional index data set for brain efficiency prediction is set to obtain;A deep learning model for brain efficiency prediction is constructed as corresponding brain efficiency prediction model;Through the way of Chinese and Western medicine examination and brain efficiency expert evaluation to pre-recruited volunteer population, model data set is constructed and is recorded as corresponding first data set;Brain efficiency prediction model is trained based on the first data set;After model training ends, brain efficiency index prediction is carried out according to the multidimensional index set of the measured person based on brain efficiency prediction model. Through the present application, the prediction efficiency and prediction accuracy can be improved.

The elevator running state cross-domain evaluation method fusing the passive domain self-adaptive technology comprises the steps that elevator running time sequence data, elevator historical running logs and expert evaluation results are collected and integrated, and a source domain elevator data set is formed; the elevator operation time sequence data are preprocessed, feature extraction is conducted on the elevator operation time sequence data and elevator historical operation logs, and dynamic features and static features are obtained; building an elevator running state evaluation model, and training the model by taking the dynamic characteristics and the static characteristics as input; historical operation logs and elevator operation time sequence data of the elevator in the new scene are collected to serve as target domain data, and dynamic features and static features of the elevator in the new scene are extracted; and a label stability evaluation mechanism is utilized to set pseudo labels for elevator samples of the target domain, and the dynamic characteristics and static characteristics of the elevator in the new scene are adopted to carry out migration training on the elevator running state evaluation model.

This invention discloses a dynamic risk assessment method and system for storage tanks, comprising the following steps: S1, identifying potential risk sources of the storage tank, taking tank leakage as the assessment object; S2, inputting the potential risk sources and their possible consequences into a fuzzy Bow-Tie model to form a preliminary qualitative analysis of consequences and measures; S3, transforming the Bow-Tie model into a Bayesian network based on mapping relationships; S4, having experts score the corresponding risk sources and converting the scores into prior probabilities of the root nodes of the Bayesian network, determining the weights of each expert using the analytic hierarchy process (AHP), and converting the expert evaluation results into fuzzy probabilities to obtain the prior probabilities of the root nodes and determine the conditional probability tables of other nodes; S5, calculating the posterior probabilities and analyzing and determining the priority relationships of failure modes; S6, providing corresponding risk control measures based on the priority judgment results. This method realizes management from risk source identification to control measure output, overcoming the problem that traditional methods cannot cope with complex dynamic environments.

The present disclosure provides a threshold adaptive network transaction risk early warning method and system based on expert feedback, relating to the technical field of network transaction monitoring, comprising: based on network transaction data, calculating the risk value of all or part of the specified type of network transaction risk; the intelligent agent observes the time sequence change characteristics of the network transaction risk and constructs the network transaction risk early warning state, executes the action selection strategy according to the early warning state and outputs the corresponding early warning threshold optimization action; based on the early warning threshold optimization action, the threshold parameters of the early warning strategy are adjusted to generate an updated early warning strategy; according to the updated early warning strategy, the current network transaction risk value is compared with each level of early warning threshold, the corresponding network transaction risk early warning level is calculated, and the early warning result is output; collecting expert evaluation feedback on the early warning result and training the reward model to guide the intelligent agent to continuously learn the early warning threshold adaptive strategy. The present disclosure can perceive the time sequence fluctuation of the network transaction risk situation.

This invention relates to the field of intelligent fire protection technology, specifically to a model knowledge update and question-answering method that integrates retrieval enhancement and feedback learning. Based on a user-inputted fire-related query, this method retrieves the latest relevant background information from a private vector knowledge base and combines it into enhanced prompts, which are then fed into a large model fine-tuned with a fire-related corpus to generate professional answers. Simultaneously, a feedback learning loop is established, generating reward signals through expert evaluation and automated rule verification, and continuously fine-tuning the model using reinforcement learning. This invention ensures the timeliness of knowledge through real-time retrieval, ensures the compliance and professionalism of answers through feedback-driven optimization, and achieves continuous system evolution through dynamic knowledge base updates and IoT integration, effectively improving the accuracy, reliability, and adaptability of professional question answering in the field of intelligent fire protection.

The application provides a communication protocol test evaluation method and device based on multi-agent cooperation, relates to the technical field of communication protocol testing, and comprises the following steps: inputting a communication protocol test text into a document preprocessing unit to obtain a text block; inputting the text block into a semantic retrieval unit to obtain protocol core data; inputting the protocol core data into a test point design unit to obtain an initial test point set; inputting the initial test point set into a test point optimization unit to obtain a final test point set; inputting the final test point set into a test case generation unit to obtain an initial test case set; inputting the initial test case set into a test case sorting unit to obtain a test mind map, sorting the initial test case set according to the test mind map, and obtaining a final test case list; performing communication protocol testing according to the final test case list to obtain a communication protocol test result; and inputting the communication protocol test result into an expert evaluation model to obtain a communication protocol test evaluation result.