21results about How to "Comprehensive evaluation results" patented technology

The invention belongs to the technical field of spectral analysis, and discloses a spectral analysis and image recognition combined intelligent stoma evaluation system and method.A three-dimensional scanning module captures the three-dimensional form of a stoma and the three-dimensional form of surrounding tissue of the stoma through the high-precision laser or structured light scanning technology; the spectral analysis module is used for accurately analyzing the color change of the stoma; the tiny color difference of the stoma area is detected to help to identify potential tissue abnormality; the image recognition and processing module is used for analyzing the collected stoma image by using a deep learning algorithm and automatically recognizing morphological characteristics of the stoma; the data analysis and feedback system is used for automatically generating a stoma health assessment report according to the collected multi-dimensional data; through a set standard reference value, an actual measurement value is compared, and a corresponding suggestion is given, for example, whether a nursing scheme needs to be adjusted or further medical intervention needs to be carried out. According to the method, the real-time state of the stoma is accurately evaluated through non-contact scanning and spectrum detection.

The application provides a multi-dimension evaluation method for an interference scene, which solves the problems of evaluation hysteresis, improves the consistency of evaluation, solves the single dimension of evaluation and the lack of consideration of terrain in the evaluation of the interference scene; the position accessibility analysis of terrain perception of a propagation path between a signal simulation device and a target device is carried out based on a digital elevation model; the device behavior compliance analysis is carried out in four dimensions of time domain, space domain, frequency domain and energy domain; if there is a moving route, the route coverage and signal continuity analysis are carried out in combination with the analysis results of the former two; finally, the analysis results of the three dimensions are weighted and fused to calculate the scene comprehensive effectiveness score and map it to high, medium and low three levels of confidence. Through the construction of the multi-dimension collaborative pre-evaluation system, the scientific and quantitative pre-evaluation of the training scene planning scheme is realized, the planning quality and efficiency are effectively improved, and the risk of waste of training resources is reduced.

The application discloses a self-adaptive multi-modal data fusion bridge health monitoring method and system, generates a response sample database through establishment of a bridge nonlinear dynamics equation, pre-processes bridge sensor data and trains a deep learning model to extract damage features, and self-adaptively optimizes model parameters; based on model output, real-time and historical data are combined to perform bridge health evaluation, and a monitoring strategy is dynamically adjusted or early warning is triggered; an edge computing device is deployed to perform pre-processing and damage identification, and long-term trend analysis is realized in cooperation with a cloud platform; macro-structure damage and micro-crack data are fused through cross-scale feature extraction; an artificial intelligence algorithm is used to generate a bridge health evaluation result, a bridge maintenance and repair scheme and a decision-level early warning signal. The application combines nonlinear dynamics modeling, self-adaptive deep learning, edge cloud collaborative computing and cross-scale analysis, improves complex damage identification precision and monitoring intelligent level, and is suitable for large-scale traffic network bridge monitoring management.

The invention discloses an evaluation method for an anti-scaling agent of oilfield produced water. The evaluation method comprises the following steps: preparing an anti-scaling agent water sample and a blank water sample by utilizing the oilfield produced water or simulated produced water; standing the scale inhibitor water sample and the blank water sample to form scales; calculating the anti-scaling rate of the anti-scaling agent by using the scale quality difference between the anti-scaling agent water sample and the blank water sample; the method solves the problem of serious evaluation distortion caused by high dilution ratio of a water sample with high calcium and magnesium ions when the scale inhibitor is evaluated by conventionally detecting the concentration change of scale-forming cations in produced water added with the scale inhibitor and not added with the scale inhibitor.

The invention discloses a loess plateau power grid facility coupling meteorological disaster risk dynamic assessment method and system. The method comprises the steps of obtaining static parameters, gridding meteorological forecast data and geographical geological data of primary equipment of a power grid in a target area; based on the static parameters, the gridded weather forecast data and the geographic and geological data, combining a pre-constructed risk assessment index model to obtain various risk indexes of the target equipment in the prediction time period; and determining the comprehensive risk level of the equipment by adopting a weighted fusion or most dangerous principle based on each risk index, and generating a risk distribution diagram and early warning information. The adaptive power grid equipment risk assessment method is constructed according to the meteorological geology characteristics of the loess plateau region, the problem of water and soil disability of a general model is solved, main meteorological disasters are comprehensively covered through five indexes, and the assessment result is more comprehensive and accurate; on the basis of weather forecast data, risk rolling assessment of several hours to several days in the future can be realized, passive response is changed into active defense, and the operation and maintenance efficiency is improved.

The application discloses a multi-dimensional chip evaluation method and device and electronic equipment, and belongs to the technical field of chip evaluation. The method comprises the following steps: managing a system through a main module, wherein the main module comprises a cluster management module, a container management module, a log module, an image management module and a system monitoring module; evaluating a chip to be evaluated through a sub-module to obtain a corresponding multi-dimensional evaluation result, wherein the sub-module comprises a training sub-module, an inference sub-module, a basic specification sub-module and an operator sub-module; and determining a comprehensive evaluation result of the chip to be evaluated based on the multi-dimensional evaluation result. The application has strong adaptability and can comprehensively reflect the performance of the chip and the ecological adaptability thereof.

This invention discloses a comprehensive assessment and evaluation method for sound environment quality, which consists of two parts: a "one-vote veto" assessment mechanism and a (sub)index assignment evaluation mechanism. The final assessment and evaluation system is based on index assignment, forming a "5+(2)x" assessment and evaluation system, which includes four steps: (1) Collect relevant data of the area to be evaluated, including functional area sound environment monitoring data, road traffic sound environment monitoring data, regional sound environment monitoring data, and noise complaint and petition case data, etc.; (2) First, determine whether the pre-set "one-vote veto" condition is met. If so, the assessment result is determined to be unqualified, and the evaluation index is assigned a value of 0; (3) If the "one-vote veto" condition is not triggered, based on the collected data, calculate five sub-indices: functional area sound environment compliance index DBI, road traffic sound environment intensity index JTI, regional sound environment standard index QYI, noise cross-influence intensity index JCI, and complaint and petition handling index XFI; (4) Take the arithmetic mean of each sub-indice and use it as the index evaluation result, which is defined as the sound environment quality index NQI. This invention integrates several aspects, including routine acoustic environment monitoring data, application of acoustic environment quality standard limits, demonstration of noise pollution prevention and control effectiveness, and public perception of noise impact. It can more scientifically and accurately evaluate the acoustic environment quality, improve public participation, sense of gain, and acceptance, and, based on the principle of monitoring serving management, provide data support and decision support for noise pollution prevention and control and acoustic environment quality improvement.

The application discloses a corn nitrogen reduction and biochar effect time sequence dynamic characteristic evaluation method, first, different combinations are set, chlorophyll fluorescence parameters, crown layer spectral reflectance and yield data of corn at key growth stages such as jointing stage and big bell mouth stage are collected; second, the spectral data is preprocessed, single time phase red edge characteristics are calculated, and time sequence dynamic characteristics are constructed, biochar sensitive wave bands are screened through reflectance difference percentage during growth, red edge index is designed, and fluorescence weight spectral index is constructed in combination with wide band vegetation index; then, the data is integrated to construct a multi-time phase spectral characteristic data set, a time sequence dynamic chlorophyll inversion model containing dynamic inversion, yield prediction and attribution branches is built, the former outputs chlorophyll and photosynthetic code vector at the grain filling stage, and the latter predicts yield and related parameter contribution; finally, the model is trained, the optimal matching is obtained based on the trained model, and support is provided for corn planting and fertilization decision-making.

The invention discloses a cigarette density comprehensive evaluation method based on an ideal density curve. The cigarette density comprehensive evaluation method comprises the following steps: S1, determining a division range of a tight head part and a middle section part of a standard cigarette; s2, performing density detection on a cigarette sample needing to be evaluated by using a cigarette moisture and density distribution measuring instrument; s3, middle-section density fluctuation evaluation; s4, performing tight head-middle section density matching evaluation; s5, evaluating density fluctuation between the cigarettes; s6, evaluating the density difference of the cigarettes discharged inside and outside the cigarette making machine; and S7, performing evaluation and scoring according to the four indexes. The invention aims to provide a cigarette density comprehensive evaluation method based on an ideal density curve, and the method comprises four dimensions of middle-section density fluctuation, tight end-middle-section density matching, density fluctuation among different cigarettes, and density difference between inner and outer rows of cigarettes. Therefore, the comprehensive influence of the cigarette density on physical properties and sensory quality can be comprehensively reflected.

The application discloses a mobile application platform optimization decision-making method and system based on evaluation results, and belongs to the technical field of mobile application quality management and control and intelligent optimization.The application constructs a multidimensional comprehensive evaluation system covering user experience, business energy efficiency, running performance, stability, maturity and activity, adopts a non-invasive probe to complete full-quantity data collection, realizes quantitative evaluation through a weighted comprehensive scoring algorithm, completes accurate positioning of abnormal root causes based on a coupling algorithm of an improved analytic hierarchy process-entropy weight method, automatically matches an optimization strategy library to generate a hierarchical optimization decision-making scheme, and forms a full-closed-loop management of evaluation-analysis-optimization-verification.The application solves the problems of fragmentation of the evaluation system, low accuracy of root cause positioning and lack of a closed-loop optimization mechanism in the prior art, is suitable for enterprise-level mobile application platform whole-life-cycle quality management and control, and can significantly improve application stability, operation and maintenance efficiency and user satisfaction.

The application provides a kind of urban parking management evaluation and grading method for multi-agent collaborative demand, constructs V, P, O, S, R, M six dimensions, 18 fine index system, covers resource state, operation pressure, system vitality, risk resistance, subject organization, management ability whole chain, fits multi-agent collaborative governance appeal, promotes parking management from single point evaluation to system global evaluation, the evaluation result is more comprehensive, more close to the real governance scene of city. At the same time, the index and strategy system is built with the multi-agent collaborative demand of managers, operators and users as the bottom logic, so that the evaluation is derived from the multi-agent demand, and the strategy serves the multi-agent landing, solving the problem of fragmented rights and responsibilities, mismatched measures and poor collaboration in traditional governance.

The invention belongs to the technical field of VR glasses, and particularly relates to a VR-based attention modular detection system, which comprises VR glasses, an eye myoelectricity module, a voice assistant module, an audio processing unit, a heart rate module, a central main control chip and a connection relation thereof. The eye myoelectricity module, the voice assistant module, the audio processing unit, the heart rate module and the like are arranged to collect bioelectricity signals, sound signals and heart rate information of a human body, the interest and participation degree of a testee are stimulated in cooperation with the VR glasses, it is avoided that the testee feels nervous or anxious to affect the testing result, electroencephalogram data and eye movement data are added, and the testing accuracy is improved. And a more comprehensive and more accurate evaluation result is provided.

This invention discloses an interactive sports training assessment method and system, belonging to the field of sports training assessment technology. The invention utilizes a data acquisition module to collect athletes' physical condition data, stride length data, stride frequency data, and center of gravity shift data in real time. Then, a data processing module sequentially calculates and outputs a stride length score (BH), an overall movement quality score (ZT), and a new ideal stride length (LB). new Using the results feedback and adjustment module, the new ideal stride length LB is adjusted. new The results are compared with the ideal stride length (LB) obtained from the stride length data, and the correction is evaluated. The new ideal stride length (LB) is then replaced with the new ideal stride length (LB) in the next training session. new This invention enables athletes to make targeted improvements, and reasonable stride length, coordinated stride frequency and stable body center control help improve running efficiency. The ideal stride length (LB) is optimized in real time based on the overall running motion quality, so that training can be flexibly interactive and adjusted according to the athlete's real-time performance, thereby continuously improving training effect and athletic performance.

The invention discloses a motor shell finished product detection method and system based on multi-source data analysis, and relates to the technical field of quality detection, and the main scheme is as follows: collecting multiple data of a motor shell; respectively calculating a size conformity comprehensive index, an internal structure stability index and a material performance evaluation value, further calculating a finished product comprehensive evaluation index, presetting a threshold value and judging the grade of the motor shell; a shell quality reliability index is calculated, a shell optimization potential index is calculated based on the shell quality reliability index, then a detection optimization effect index is calculated, a threshold value is preset, and the optimization effect of current motor shell finished product detection is judged; the method can comprehensively and accurately evaluate the quality of the finished product, find potential problems in time, optimize the production and detection process, and improve the overall reliability and production efficiency of the motor shell product.

The invention relates to the technical field of ovality analysis and processing decision systems, in particular to a BIM-based tunnel segment ovality repair effect evaluation system and method, and the system comprises a data collection module which is used for collecting node data in the whole life cycle of a tunnel, and constructing a tunnel multi-source heterogeneous data set; the intelligent analysis module is in communication connection with the data acquisition module and is used for receiving the multi-source heterogeneous data sent by the data acquisition module; analyzing segment ovality based on the three-dimensional point cloud data; constructing an ovality change prediction model; the processing scheme recommendation module is in communication connection with the intelligent analysis module and is used for recommending an ovality processing scheme based on the expert knowledge graph; the man-machine interaction module is in communication connection with the intelligent analysis module and the processing scheme recommendation module and is used for interactively displaying the intelligent analysis result; the method supports the input and optimization of an analysis model, can improve the processing efficiency and quality of the tunnel segment ovality problem, and can provide a new idea and tool for the overall management of tunnel engineering.

The present application belongs to the technical field of enterprise management, and specifically relates to an enterprise health assessment system based on fsQCA analysis, which realizes comprehensive and in-depth assessment of the health status of an enterprise through the organic combination of three modules of data collection, data analysis and evaluation. The data collection module can collect multi-dimensional data including employee personal characteristics, organizational environment, digital transformation characteristics, etc. The data analysis module uses the fuzzy set qualitative comparative analysis method to construct a relationship model between the condition variable and the result variable, accurately identifies the factors affecting the health of the enterprise and their configuration path. The evaluation module further generates a detailed evaluation report containing the excitation path, inhibition path and improvement suggestions according to the analysis results. The system not only provides accurate and objective evaluation results for enterprises, but also effectively guides enterprises to make strategic planning and operational management adjustments in a timely manner, and promotes the healthy and sustainable development of enterprises.

The application discloses a kind of urban rail transit signal system key risk node identification method, comprising: according to component extraction rule, the equipment or subsystem in signal system is abstracted as network node, and three kinds of connection relations of mechanical, electrical and information between components are defined;Based on network node and connection relation, the physical topology network model of communication system and signal system is respectively constructed, and the topology network reflecting system architecture and connection relation is formed;Based on topology network, the structure importance of node is calculated in combination with the local information and position information of node, and the key node with significant influence on system operation is identified.The present application can comprehensively reflect the importance of node in topology structure, and provides a reliable basic framework for risk analysis and safety evaluation of signal system.

The invention discloses a multi-layer and multi-factor prediction and evaluation method for a vibration signal state of an engine in a rising stage of a carrier rocket. Comprising the following steps: firstly, analyzing and predicting sampled historical data in a short time by using a more effective feature extraction method of an LSTM deep network, and obtaining higher prediction precision at the same time; a method based on comparative statistics of predicted waveforms and ideal waveforms is adopted, and higher evaluation precision is obtained; obtaining weight factors of various vibration signals in combination with an analytic hierarchy process; and finally, obtaining a health value of the research target from bottom to top by adopting a fuzzy comprehensive evaluation method. The method is suitable for complex fuzzy systems such as carrier rockets, health scores are obtained through historical data interception, data processing, data prediction and comprehensive evaluation and are transmitted back to a ground test launch control platform, ground monitoring personnel can conveniently and accurately master the flight state of the rocket after launch, and the method is used for making rocket launch and flight strategies.

The invention discloses a cigarette enterprise equipment health degree calculation method based on multi-dimensional dynamic evaluation, and belongs to the technical field of intelligent operation and maintenance of industrial equipment, and the method comprises the following steps: 1, constructing an equipment health degree hierarchical evaluation model; step 2, free configuration of configuration indexes; step 3, dynamic weight distribution; 4, multi-source data fusion and normalization are carried out; and 5, calculating the overall health degree of the equipment. According to the method, all aspects of equipment management are comprehensively covered through six dimensions, so that the evaluation result is more comprehensive and more accurate; dynamic weight distribution is adopted, so that an evaluation result better fits the actual risk of the equipment; specific secondary evaluation indexes are configured for each dimension in a free configuration mode, so that the method can be flexibly adapted to various equipment in a cigarette factory, the applicability is higher, and the operation and maintenance cost is reduced; and finally, through drilling analysis, operability is improved, and production safety and quality are guaranteed.

This invention discloses a crowdsourcing quality and safety assessment method based on federated learning with blockchain assistance. Task publishers post task information on a crowdsourcing platform according to their needs, select a corresponding federated learning model, and calculate and upload evidence information to the blockchain. Task executors select tasks of interest, accept them, calculate evidence information, and upload it to the blockchain. Task executors complete the tasks according to the task requirements, obtain task data, use it to train a federated learning model, encrypt the task data, send it to the task publisher, add noise to the model parameters using differential privacy, and upload it to the blockchain along with calculated evidence information. The task publisher evaluates the quality of the task data submitted by the task executors and uploads the evaluation ranking results to the blockchain. This invention trains task models for specific task types using federated learning, utilizes blockchain to record important information, making the results traceable and verifiable; simultaneously, it uses differential privacy to add noise to the model update parameters, effectively preventing attackers from deducing the task executor's original data based on the model parameters.

This invention discloses an accounting simulation teaching system and method based on virtual reality and knowledge graphs. The system includes: a virtual reality module for constructing an immersive accounting practice environment; a knowledge graph module storing entities, relationships, and rules constructed based on accounting standards and business logic for logical verification of user operations; and an error handling and reinforcement learning subsystem, which includes: an error recording unit for capturing and storing the error's operational context information when a user operation is determined to be erroneous by the knowledge graph module. This invention has the advantages of strong immersion, real-time and accurate feedback, personalized teaching paths, structured knowledge system, and a trustworthy and collaborative learning process.