17 results about "Project assessment" patented technology

The invention discloses an AI-based digital project performance evaluation data processing method and system, and relates to the technical field of artificial intelligence and digital project management, and the method comprises a multi-source data collection module which is used for obtaining data; the entity alignment module is used for establishing an association relationship among cross-system data entities; the dynamic index generation module is used for dynamically adjusting the evaluation index weight by utilizing a reinforcement learning framework; the efficiency prediction module is used for modeling a task dependency relationship according to the time sequence diagram convolutional network and outputting a delay risk probability; and the visual interface is used for displaying the data. According to the method, cross-system entity alignment, dynamic index weight adjustment, task delay risk prediction and root cause analysis are realized through AI technologies such as BERT semantic matching and a graph neural network, visual data display and interaction functions are provided by virtue of a visual interface, the problems of data dispersion, index static state, risk lag and the like in traditional project evaluation are solved, and the project evaluation efficiency is improved. And the decision support capability of project management is improved.

The invention relates to an electric power infrastructure project assessment model construction method and system for risk assessment. The method comprises the steps of obtaining historical risk data and real-time monitoring data of a to-be-assessed electric power infrastructure project; preprocessing the historical risk data and the real-time monitoring data to obtain a standardized data set; performing feature engineering processing on the standardized data set, extracting statistical features, time sequence features and associated features, and performing screening to obtain key risk features; constructing feature vectors according to the key risk features; performing parameter initialization on a preset machine learning algorithm according to the dimension of the feature vector, and constructing an initial risk assessment model; and training and optimizing the initial risk assessment model by using the standardized data set to obtain a target risk assessment model which is used for performing risk assessment on the real-time monitoring data of the to-be-assessed power infrastructure project and outputting a risk assessment result. Compared with the prior art, the method improves the comprehensiveness and flexibility of project risk assessment.

The embodiment of the invention provides a project deviation degree evaluation method and device, computer equipment, a medium and a product, and the method comprises the steps: determining a current progress stage of a target project according to progress feature data of the target project; based on the current progress stage, determining an association degree between the target project and other projects and a qualitative evaluation level of the target project; according to the correlation degree and the qualitative evaluation level, adjusting an evaluation index coefficient of the target project; and determining the deviation degree of the target project according to the operation data of the target project and the adjusted evaluation index coefficient. In the project proceeding process, the progress of the project is recognized in real time, the corresponding evaluation index weight is matched, it can be ensured that the evaluation result is matched with the actual state of the project, and evaluation deviation caused by stage mismatching is avoided. In addition, by adding a collaborative index, collaborative recommendation among multiple projects is concerned, and the comprehensiveness of project evaluation is improved.

The invention belongs to the technical field of ecological data processing. The invention provides an ecological environment admission intelligent analysis risk assessment method and system based on a large model. An integrated scheme of multi-source data acquisition and targeted preprocessing, large model driven knowledge extraction, dynamic ecological environment access knowledge graph construction, project information intelligent analysis, multi-dimensional intelligent matching, risk inference engine iterative reasoning, structured report generation and knowledge and rule base continuous optimization is adopted. A full-process automatic ecological environment admission analysis and risk assessment system is constructed, the core problems that traditional ecological environment admission assessment highly depends on manpower, is low in efficiency and is non-uniform in standard are solved, and the technical defects that an existing system lacks deep text understanding and automatic reasoning ability, knowledge updating lags behind and complex correlation analysis is difficult are overcome. Through close connection and data circulation of all links, the automation degree and operation efficiency of the assessment process are greatly improved, the consistency and objectivity of assessment standards of similar projects are ensured, and the comprehensiveness and accuracy of risk identification are improved.

This invention specifically relates to a method for full lifecycle management and evaluation of enterprise information technology projects, belonging to the field of information technology project management technology. It includes: generating a software artifact knowledge graph based on software artifact information and its relationships contained in the four-dimensional quality evaluation index matrix, using requirement items, software architecture modules, code files, and test cases as entity nodes, and traceability and dependency relationships between entities as association edges. In this invention, a four-dimensional quality evaluation index matrix covering requirements, software architecture, code, and testing is established, expanding the project evaluation perspective from schedule and workload indicators to quality indicators within software engineering, enabling the quantitative identification of quality problems hidden beneath normal progress appearances.

The invention relates to a method and device for providing decision reference information of a scientific and technological innovation project, equipment, a storage medium and a program product, and relates to the technical field of computers. By adopting the method, the scientificity and reliability of scientific and technological innovation project evaluation decision can be improved. The method comprises the steps of obtaining a project data set of a scientific and technological innovation project, and performing data cleaning on the project data set to obtain to-be-analyzed target project data; analyzing the target project data through a data analysis algorithm to obtain an analysis result, and performing quantitative scoring on each evaluation index in the evaluation index system according to the analysis result to generate a quantitative scoring result; determining a weight vector of each evaluation index by adopting an analytic hierarchy process, and comprehensively evaluating the scientific and technological innovation project by adopting a fuzzy comprehensive evaluation method according to the weight vector and the quantitative scoring result to obtain a comprehensive evaluation result vector; and generating decision reference information of the scientific and technological innovation project according to the comprehensive evaluation result vector.

The application discloses a reservoir temporary inundated area risk assessment method based on scheduling simulation and relates to the technical field of water conservancy project assessment, and comprises the following steps: step one, data collection and environment modeling; step two, reservoir hydrological dynamics and risk assessment calculation; step three, loss calculation; and step four, temporary inundated area risk assessment. The reservoir temporary inundated area risk assessment method based on scheduling simulation guarantees security and scientificity, optimizes the safety management of the inundated area through risk grading and control measures, and enhances the emergency response capability of the reservoir under high water level scheduling.

An object of a system according to an embodiment is to improve the efficiency of employee performance evaluation.SOLUTION: A system includes a self-evaluation analysis part, a calendar connection part, a project evaluation part, and a target achievement evaluation part. The self-evaluation analysis unit analyzes the employee's self-evaluation. The calendar connector organizes the evaluation scores based on the self-evaluation analyzed by the self-evaluation analyzer. A project evaluation part evaluates the project on the basis of the evaluation points arranged by the calendar connection part. A target achievement evaluation part evaluates the degree of achievement to the set target on the basis of the information of the project evaluated by the project evaluation part.SELECTED DRAWING: Figure 1

The invention relates to the technical field of project evaluation, in particular to a wind-solar complementary project collaborative benefit quantification and economy combined evaluation method, which comprises the following steps of: performing comprehensive judgment on collaborative operation basic data and economy basic data based on a preset evaluation threshold value to obtain an initial combined evaluation grade; performing coupling simulation based on the wind and light resource coupling distribution to obtain a collaborative benefit simulation result; determining a current predicted collaborative benefit of the project based on the collaborative benefit simulation result; and determining a joint evaluation result of the project based on the collaborative operation basic data, the economic basic data and the current predicted collaborative benefit. According to the method, an iterative algorithm and an error verification mechanism are adopted in the evaluation process, the prediction model can be continuously optimized according to the actual change condition, the reliability of the evaluation result is ensured, the dynamic updating mode can adapt to the change of the actual condition, the evaluation standard can be adjusted in time, and the adaptability and flexibility of project operation are improved.

The invention discloses a project progress intelligent evaluation method and device and a medium, and the method comprises the steps: obtaining multi-modal evidence data related to a project progress, and carrying out the semantic alignment of the multi-modal evidence data, and obtaining the association data of an evidence and a progress node standard; obtaining project feature data, encoding the project feature data into a multi-dimensional project feature vector, processing the project feature data based on a multi-level analysis and expert model dual-driven project dynamic weight calculation principle, and generating dynamic weight data of a project; constructing project knowledge graph data based on a total factor knowledge graph reasoning principle, applying a predefined reasoning rule to the project knowledge graph data, performing progress logic verification and resource matching analysis, and generating progress evaluation result data; and calculating project health degree score data based on the progress evaluation result data, and generating project evaluation report data to output the project health degree score data and the project evaluation report data.

The embodiment of the invention discloses a project evaluation method and device and electronic equipment, and the method comprises the steps: determining evidence information related to a project evaluation index according to a government affair data development and utilization case; determining an index evaluation score corresponding to the project evaluation index based on the evidence information; performing clustering processing on the index evaluation score corresponding to the project evaluation index to obtain a plurality of classes, and determining a first evaluation score corresponding to each class according to the index evaluation score corresponding to each class; determining a target score corresponding to the project evaluation index according to the number of the index evaluation scores corresponding to the project evaluation index, the number of the index evaluation scores corresponding to each class and the first evaluation score corresponding to each class; and according to the target score corresponding to the project evaluation index, performing development and utilization value and / or development and utilization risk evaluation processing on a to-be-evaluated government affair data development and utilization project to obtain a project evaluation result.

The invention discloses a feature contribution analysis-based project evaluation method and device, a medium and a product. The method comprises the following steps of: constructing a standardized feature vector according to original data of a to-be-evaluated project; according to the standardized feature vector, an improved decision tree evaluation model is adopted to generate an evaluation result and a decision path of the to-be-evaluated project; wherein the improved decision tree evaluation model is obtained by improving a decision tree model by adopting a cost complexity pruning function and a feature weight adjustment factor; performing feature contribution analysis on each feature in the standardized feature vector according to the decision path to obtain a contribution vector; adopting a preset text template and the contribution vector to generate an interpretable text; and generating an evaluation report according to the evaluation result, the decision path, the contribution vector and the interpretability text. A pruning constraint and weight adjustment mechanism is introduced on the basis of a traditional decision tree, and the prediction precision and project interpretation ability of the model can be improved.

The invention relates to the field of project evaluation, in particular to an AI-driven intelligent evaluation system for innovation and entrepreneurship practice projects, which comprises the following steps: extracting information keywords corresponding to practice projects, performing retrieval in a project database, determining the content overlap ratio with a plurality of projects and the keyword overlap number, and constructing a fuzzy matching project set; identifying a farthest matching time difference between the practice item and a plurality of fuzzy matching items, calibrating a farthest matching time interval, calculating an innovation fuzzy characterization value of the practice item based on fuzzy matching features, dividing innovation degree categories of the practice item, adaptively evaluating and analyzing the practice item, and determining the innovation degree of the practice item. Comprising the following steps: based on specific keywords of a practice item relative to a plurality of fuzzy matching items in a fuzzy matching item set, carrying out joint evaluation on the specific keywords; and determining a fuzzy innovation level of the practice item according to the innovation fuzzy representation value, and storing the fuzzy innovation level in a database. According to the invention, the precision and efficiency of practical project evaluation are improved.

The invention discloses a project evaluation method and device based on a large language model, electronic equipment and a storage medium, and relates to the technical field of project management, and the project evaluation method based on the large language model comprises the steps: obtaining multi-source project data corresponding to a target project, and carrying out the preprocessing, inputting text type data and external data in the preprocessed multi-source project data into a pre-trained first large language model, and extracting and outputting multiple evaluation indexes corresponding to a target project and corresponding weights by the first large language model; and after a confirmation instruction corresponding to the output content of the first large language model is received, inputting the preprocessed multi-source project data, each evaluation index and the weight corresponding to each evaluation index into a pre-trained second large language model to obtain a score, a comprehensive score and the like of the target project in each evaluation index. The technical problem that a traditional project evaluation scheme is poor in accuracy and scientificity is solved.

The invention relates to the technical field of power distribution network planning and evaluation, in particular to a network frame project evaluation method and device for a power distribution network, and the method comprises the steps: integrating SCADA, AMI and OMS multi-source data with a power grid topological graph, and determining a network frame project by taking a medium-voltage line or a transformer substation power supply unit as an object; configuring necessary toughness disaster resistance dimensions and selectable economic investment, user service and operation and maintenance digitization dimensions, and setting quantitative indexes for the dimensions; constructing a secondary weight system through an analytic hierarchy process, and correcting an evaluation coefficient in combination with an entropy evaluation method and a dimension weight; and calculating a comprehensive evaluation result and contribution degrees of all dimensions to generate a visual report, and outputting optimization and transformation suggestions or realizing multi-project transverse optimization. A matching device comprises an edge calculation module, a GPU acceleration module and the like, and efficient evaluation is guaranteed. According to the method, evaluation objectification, dimension comprehensiveness and result landing are realized, and the scientificity and accuracy of power distribution network investment decision are effectively improved.

Provided is a method apparatus for evaluating a project based on a large model, an electronic device, and a storage medium, relating to the field of computer technology, and in particular to fields of software and hardware project development, software and hardware project evaluation, machine learning, large model and other applications. The method includes: obtaining an evaluation intention for a target project; where the evaluation intention is used to request an evaluation of the target project under a specific evaluation indicator; obtaining an initial evaluation result for the target project under the specific evaluation indicator based on the evaluation intention using the large model; and obtaining a target evaluation result for the target project based on the initial evaluation result.

The invention relates to a city update project evaluation method, electronic equipment and a storage medium, and the method comprises the steps: obtaining project data corresponding to a plurality of city update projects of a target city, the project data corresponding to any city update project comprises multi-source data before the implementation of the city update project and multi-source data after the implementation of the city update project; according to the project data corresponding to each of the plurality of city update projects, determining multi-dimensional evaluation results before and after each implementation of the plurality of city update projects from a plurality of evaluation dimensions, the plurality of evaluation dimensions including scale development intensity, job-housing population features, service function features, project vitality and popularity, and social perception evaluation; and determining project effect evaluation results of the plurality of city update projects according to the multi-dimensional evaluation results before and after respective implementation of the plurality of city update projects. Therefore, the implementation effect of the city updating project can be comprehensively evaluated from multiple evaluation dimensions in a standardized and systematic manner.