Fuzzy Comprehensive Evaluation Algorithm Research Articles

An Adaptive Trust Evaluation Model for Detecting Abnormal Nodes in Underwater Acoustic Sensor Networks.

Underwater acoustic sensor networks have a wide range of applications in both civil and military fields, but the complex and changing underwater environment makes them vulnerable to multiple security threats. Trust mechanisms are effective ways to enhance network security and reliability. In order to improve the accuracy of trust evaluation and the detection rate of abnormal nodes, this paper proposes an adaptive trust evaluation model based on fuzzy logic. This model adopts a variable weight fuzzy comprehensive evaluation algorithm to dynamically adjust the weights of three direct trust indicators to ensure the accuracy of direct trust evaluation. Then, it uses fuzzy closeness to eliminate unreliable recommendation trust and adjusts the weight of recommendation trust through deviation to improve the accuracy of indirect trust. The simulation results show that the model can effectively improve the accuracy of trust evaluation and the detection rate of abnormal nodes. Especially when the link quality is unstable, the success rate of detecting abnormal nodes in this model is improved by more than 10% compared with the existing trust model.

Research on the reform and effect evaluation of three-dimensional motion animation blended teaching based on fuzzy evaluation model

Abstract This paper combines the teaching of a 3D animation course with the blended teaching mode and constructs a framework for the design of 3D animation blended teaching reform. Based on the fuzzy comprehensive evaluation algorithm, we adopt qualitative and quantitative methods to determine the evaluation index system of teaching reform, divide the course teaching objectives, teaching content, learning resources, online learning and teaching design and classroom organization into five first-level indexes, establish the weights of the evaluation index system, and complete the construction of the fuzzy comprehensive evaluation system of 3D animation blended teaching. Examine the design and teaching effects of 3D animation that blends learning from different dimensions, and examine the correlation between learners’ multidimensional recognition of teaching reform and its learning impact. By combining the weights of each index, the fuzzy comprehensive evaluation results are obtained by determining the affiliation degree of each index using the fuzzy statistical method. The operation results show that the fuzzy comprehensive evaluation scores of the five first-level indicators of teaching reform are 0.754546, 0.69943, 0.638926, 0.66888, and 0.5966. It can be seen that the comprehensive evaluation results of the five aspects have achieved good results. The evaluation of teaching reform’s effects can be targeted and feasible using a fuzzy comprehensive evaluation model.

Online and offline hybrid teaching evaluation and monitoring system based on hierarchical analysis method and fuzzy comprehensive evaluation algorithm

Online and offline hybrid teaching evaluation and monitoring system based on hierarchical analysis method and fuzzy comprehensive evaluation algorithm

Analysis of the application of BIM combined with GIS in engineering digital management

Abstract This study centers on the application of digital intelligence technology in project management, takes the geohazard project in Z area as the research object, and evaluates and predicts the grade of the danger of slope disaster and mudslide disaster in this area. The study begins with an in-depth analysis of the integrated fusion of BIM and GIS technologies. The integrated assessment and prediction model of geologic hazards was constructed using fuzzy comprehensive evaluation and support vector machine algorithm. The study unfolded the analysis of the hazard class and risk prediction of geohazards. The results showed that most of the hazard classes in slope hazards were assessed as low danger, accounting for 33.33%. Meanwhile, about 70% of the mudslide hazards were assessed to have a low to medium hazard rating. Regarding risk prediction, the prediction accuracy of slope and mudslide hazards reached 89% and 90%, respectively. In addition, the detection rate of all geohazards in the ROC (receiver operating characteristic) curve was above 85%, while the false alarm rate remained between 14% and 22%. This result verifies the accuracy of the model in geohazard risk prediction. The comprehensive assessment and prediction model proposed in this paper will help the risk assessment and prediction of geohazards, provide adequate technical support for managing disaster information, and enhance the science and rationality of disaster prevention and mitigation.

Influencing Factors and Realization Strategies of Teachers’ Professional Development in Higher Vocational Colleges and Universities Based on the Background of Deep Learning

Abstract The fuzzy comprehensive evaluation algorithm is employed in this paper to evaluate teachers’ professional competence and improve the traditional evaluation system to construct a comprehensive evaluation system. According to the Zagan theory, twenty-three influencing factors of teachers’ professional development were screened, and five main influencing factors were derived after exploratory factor analysis and structural equation test. Countermeasures and suggestions were proposed after analyzing the factors that affect the professional development of teachers in higher vocational colleges. The results show that the model KMO value is 0.923, Bartlett’s spherical test chi-square value is 2712.752, and the significance probability value P=0.000<0.005 is statistically significant. The correlation coefficients between the five main factors are in line with the condition of correlation attribute defined among the factor analysis variables, with a range of 0.37 to 1.00. The optimization countermeasures proposed in this paper have important theoretical significance and practical significance for the professional development of teachers in higher vocational colleges.

Innovation of tax incentives in the context of integration of traditional industries and digital economy

Abstract With the development of the digital economy, the innovation of the tax preference method is necessary. This paper integrates traditional industries with the digital economy through digital technology, standardizes the tax preference data of digital industries by using a fuzzy comprehensive evaluation algorithm, and builds an innovative mechanism of tax preference by establishing two weighting indicators of tax relief ratio and Q value (tax relief locational entropy) through data feedback. To ensure the accuracy of the feedback indicators, the full-factor algorithm is invoked to detect the intensity of the mechanism’s preferences in the digital industry. To verify the effectiveness of the mechanism, the results of the practical analysis show that after the innovation mechanism constructed in this paper is put into practice, the proportion of tax breaks in two digital industries, manufacturing and industry, increases by 29% and 34%, respectively, and the Q values of the five industries increase by about 4.2% on average, and the yields all increase by about 5.12 percentage points. This illustrates that the tax preference innovation mechanism constructed in this paper can accelerate the economic development of industries and is conducive to giving full play to the positive incentive effect of tax preference on their material benefits.

A study on the application of using big data information technology to implement physics laboratory courses in universities

Abstract In today’s fast development of big data information technology, the traditional physics experiment method is difficult to adapt to the new curriculum reform physics experiment course objectives. The key topic of concern today is how to use big data information technology and physics experiment course integration for teaching. This study mainly uses the fuzzy comprehensive evaluation algorithm in big data information technology to study and analyze the physics laboratory courses in colleges and universities. Firstly, according to the principles and methods of the fuzzy comprehensive evaluation method, the model of a fuzzy comprehensive evaluation of university physics laboratory teaching is established, and the index system and evaluation level criteria of university physics laboratory teaching are established. Then the weights of each factor of the index system were determined using fuzzy comprehensive evaluation, and the evaluation results combining qualitative and quantitative were obtained by processing the data. Finally, the results were obtained regarding teaching attitude, teaching content, and teaching effect: the weights of good 55%, 64% and 38% performed better than other evaluation grades. Regarding teaching implementation: 54% weight of good evaluation is greater than other evaluation grades. From the evaluation grade, the average weight of a good grade is 48.25% greater than the other three categories, and the weight performance is better. This study is conducive to improving the experimental application ability of college students and thus has important historical significance for the development of physics in China.

Analysis of response strategies for triple La Niña events based on fuzzy evaluation algorithm

The climate anomalies caused by La Niña events have caused some economic losses and human casualties in several regions around the world. In this paper, we first visualize and analyze the climate data of four representative countries to obtain the impact of La Niña on different countries. Then a BP neural network model is built to predict the probability of La Niña events in different regions. Finally, taking six different provinces in southern China as examples, an indicator system is established, a fuzzy comprehensive evaluation algorithm is used to summarize the impacts of different regions and indicators under a La Niña event, and practical response strategies are proposed.

A recommendation management defense mechanism based on trust model in underwater acoustic sensor networks

Underwater acoustic sensor networks (UASNs) have been applied in many civilian and military scenarios, but it is vulnerable to various security threats due to the broadcast transmission characteristics and the environment in which they are located. Trust management mechanism has been proven to be an effect way to improve network security. However, in the trust assessment process, some nodes may provide false suggestions, which will lead to trust conflicts and affect the normal operation of the trust mechanism. To screen out unreliable recommendations and dishonest nodes in the network and avoid potential dangers, a recommendation management trust mechanism based on collaborative filtering and variable weight fuzzy algorithm (CFFTM) is proposed in this paper. First, three kinds of evidence of trust: communication-based evidence, data-based evidence, and energy-based evidence are select as indicators. Then the variable weight fuzzy comprehensive evaluation algorithm is applied to calculate the direct trust value of the node. Secondly, in order to quantify the honesty ability of nodes, honesty degree is defined. Then the overall recommendation trust value of the node is obtained using the proposed collaborative filtering algorithm. The simulation results show that the mechanism can well filter out unreliable recommendations and improve the recognition rate and stability of the trust model under typical attack scenarios.

Online and offline hybrid teaching evaluation and monitoring system based on hierarchical analysis method and fuzzy comprehensive evaluation algorithm

Online and offline hybrid teaching evaluation and monitoring system based on hierarchical analysis method and fuzzy comprehensive evaluation algorithm

Study on Employee Performance Evaluation Based on Adaptive Feature Selection Fuzzy Algorithm

In our study, in terms of performance evaluation methods, the performance evaluation algorithm based on genetic algorithm and fuzzy comprehensive performance evaluation algorithm is introduced, their advantages and disadvantages are compared and analyzed, and the design idea of fuzzy performance evaluation algorithm based on compound elements is proposed. It can be divided into seven steps: first, clarify the evaluation purpose and object; second, select the optimal evaluation mode and method; third, compile the evaluation index system; fourth, it is to collect information extensively; fifth, the evaluation adopts a variety of methods, multiple angles, and multiple sides to collect materials so that the conclusion of the evaluation has sufficient factual basis; the sixth is to process the information and make a comprehensive evaluation; the seventh is to analyze the results and write an evaluation report. Based on the existing algorithms, the fuzzy performance evaluation algorithm based on compound elements is studied, and the detailed design of the algorithm is presented. Through the comparison and analysis of the performance evaluation algorithm based on compound elements and the performance evaluation algorithm of specific elements, the superiority of the performance evaluation algorithm based on compound elements is experimentally verified by comparing the operation time and classification accuracy. The performance evaluation system based on the performance evaluation algorithm designed in this study, combined with the official business of the performance evaluation system, modularizes the administrative management activities of the enterprise, digitizes the electronic office information, and conducts in-depth exploration of the unstructured natural language. A real-time performance evaluation system based on the arrangement of corporate administrative activities has been established. By designing and implementing a performance-assisted analysis system based on text content analysis, which is suitable for performance evaluation systems, it solves the imperfect problem of performance evaluation based on electronic enterprise administrative management.

Formative Assessment of College English Autonomous Learning Based on Fuzzy Comprehensive Evaluation Algorithm

With the rapid development of computer networks and multimedia technology, independent e-learning has become an integral part of modern education. However, the allocation of time and space for teaching and learning, the lack of instruction and guidance necessary for self-directed learning for students, and the development of e-learning are becoming increasingly problematic. Because of this, this thesis uses guided evaluation to determine the impact of improving the quality of Student learning. Firstly, under the background of college English web-based autonomous learning, this paper constructs a formative assessment index system and then combines the formative assessment with fuzzy comprehensive evaluation algorithm to form a formative assessment of college English web-based autonomous learning. Fuzzy comprehensive evaluation is an important application of analyzing complex fuzzy systems using the principle of fuzzy transformation. The simulation uses the online learning English behavior of college students to carry out an example evaluation. The results show that students can find their own shortcomings in network autonomous learning, which can be improved in later learning.

The Analysis of Two-Way E-Commerce Credit Evaluation Model Based on the C2C Mode

As an important mode of e-commerce, C2C has become a trading mechanism favored by consumers. However, for C2C transaction in a virtual environment, there is an issue of congenital transaction asymmetry, leading to increased uncertainties and transaction risks as well as credit speculation, false transactions and other credit problems. These problems not only affect the development of enterprises to a large extent, but also hinder the development of e-commerce ultimately. In order to guarantee the safety of both transaction parties, it is particularly important to establish a sound credit evaluation system for shopping sites. Through the analysis of the shortcomings of the existing C2C e-commerce credit evaluation model, this paper proposes a two-way e-commerce credit evaluation model based on the C2C mode. Firstly, a cross-platform two-way credit rating center with a unified rating standard was constructed; secondly, the credit evaluation indicator was reset and revised; then the credit rating of buyers and sellers was unified by combining fuzzy comprehensive evaluation algorithm and

Defect recognition and condition assessment of epoxy insulators in gas insulated switchgear based on multi-information fusion

Partial discharge (PD) is one of the main reasons of insulation deterioration in power equipment. How to efficiently and accurately recognize as well as assess the PD is an important guarantee for the stable operation of power equipment. Aiming at the problems of low accuracy of single information defect recognition and condition assessment results, the PD experiments about different typical defects of epoxy insulators are carried out in this paper. On this basis, different ultra high frequency (UHF) and ultrasonic feature information are extracted from time resolved partial discharge (TRPD) and phase resolved partial discharge (PRPD) analysis modes. Furthermore, an SDAE-LDDC multi-information fusion algorithm is built to recognize the defect types, with excellent recognition accuracy (over 94%). Based on the pulse current signal, the severity of PD was classified. The feature information that successfully assesses the severity of PD is selected by combining the maximum correlation and minimal redundancy criterion (m-RMR) with support vector machine (SVM). The performance of selected feature information is tested by fuzzy comprehensive evaluation algorithm, and the assessment results of different feature information are combined using the improved Dempster/Shafer (D-S) evidence theory, which improves the accuracy of condition assessment.

Research on Safety Evaluation of Commercial Vehicle Driving Behavior Based on Data Mining Technology

The arrival of big data era of internet of vehicles promotes the rapid development of logistics industry, which also indirectly leads to the high traffic accident rate, resulting in huge casualties and property losses. Driving behavior is considered the most central factor leading to traffic accidents. Therefore, a scientific and effective method for evaluating the safety of commercial vehicle driving behavior is urgently needed. In this study, a comprehensive evaluation model of driving behavior security based on multimembership function is proposed, and entropy weight method (EWM), analytic hierarchy process (AHP), and fuzzy comprehensive evaluation algorithm are integrated. Firstly, the evaluation system of commercial vehicle safety of driving behavior is established. Secondly, the weight vector of each evaluation index is determined by combining EW-AHP to eliminate the subjectivity of the traditional AHP algorithm. Then, the fuzzy comprehensive evaluation matrix is calculated based on the multimembership function and fuzzy mathematics theory, and the quantitative evaluation of driving behavior safety is realized based on the matrix. Finally, the real road vehicle driving data and driving behavior data are verified by experiments. The experimental results show that the model can accurately and reasonably evaluate the safety of driving behavior, which is of great significance to improve road traffic safety.

A Study on the Quality Evaluation of English Teaching Based on the Fuzzy Comprehensive Evaluation of Bat Algorithm and Big Data Analysis

In this paper, the fuzzy comprehensive evaluation model based on the bat algorithm quantifies the qualitative evaluation effectively and provides a feasible and convenient English teaching quality evaluation system by combining quantitative evaluation with objective index data. Firstly, the English teaching quality evaluation model is constructed based on the fuzzy comprehensive evaluation analysis method and the weight values of each factor are calculated; secondly, the three types of data in the model are processed separately. This includes standardizing the data of objective indicators such as students’ course grades and weakening the influence of course difficulty on this indicator. The fuzzy comprehensive evaluation model based on the bat algorithm quantifies the qualitative evaluation to make the calculated comprehensive evaluation of English teaching quality more comprehensive and objective; then the comprehensive calculation of English teaching quality evaluation is completed, and the English teaching quality evaluation model is constructed by extracting keywords based on the qualitative evaluation; finally, a runnable English teaching quality evaluation system is designed and implemented. A fuzzy comprehensive evaluation algorithm based on improved bat algorithm optimization is proposed. The algorithm uses the improved fuzzy comprehensive evaluation algorithm to optimize the initial clustering centers and adopts a new objective function to guide the clustering process, thus improving the clustering quality of the fuzzy comprehensive evaluation algorithm. Comparative analysis through models shows that the improved algorithm improves the clustering accuracy to a certain extent when compared with the traditional fuzzy comprehensive evaluation clustering algorithm for analysis. The bat algorithm is one of the stochastic global optimization models. It can take advantage of the group, integrate global search and local search, and achieve rapid convergence. Therefore, it plays an important role in optimizing the evaluation of English teaching quality. This study enriches the theoretical study of English teaching quality evaluation to a certain extent and can play a role in strengthening and improving English teaching quality evaluation at the present stage.

Coating matching recommendation based on improved fuzzy comprehensive evaluation and collaborative filtering algorithm

Coating matching design is one of the important parts of ship coating process design. The selection of coating matching is influenced by various factors such as marine corrosive environment, anti-corrosion period and working conditions. There are also differences in the coating performance requirements for different ship types and different coating parts. At present, the design of coating matching in shipyards depends on the experience of technologist, which is not conducive to the scientific management of ship painting process and the macro control of ship construction cost. Therefore, this paper proposes a hybrid algorithm of fuzzy comprehensive evaluation and collaborative filtering based on user label improvement (IFCE-CF). Based on the analytic hierarchy process (AHP), the evaluation index system of coating matching is constructed, and the weight calculation process of fuzzy comprehensive evaluation is optimized by introducing the user label weight. The collaborative filtering algorithm based on matrix decomposition is used to realize the accurate recommendation of coating matching. Historical coating process data of a shipyard between 2010 and 2020 are selected to verify the recommendation ability of the method in the paper. The results show that using the coating matching intelligent recommendation algorithm proposed in this paper, the root mean square error is < 1.02 and the mean absolute error is < 0.75, the prediction accuracy is significantly better than other research methods, which proves the effectiveness of the method.

Application of Fuzzy Evaluation in Comprehensive Quality Evaluation of Higher Education Students

Scientific and reasonable evaluation of the comprehensive quality of higher education students provides a guarantee for the pertinent development of quality education in colleges, and offers an aid for students to determine goals and directions of development. Therefore, this paper first constructs an evaluation index system (EIS) for the comprehensive quality of higher education students, and then builds up an evaluation model for that quality based on fuzzy comprehensive evaluation (FCE). The FCE algorithm was designed in details, and applied to a real example. The application results show that the FCE can scientifically evaluate the comprehensive quality of the students from multiple aspects and levels. The research overcomes the difficulty in the comprehensive quality evaluation of college students, and enriches the theoretical and practical results in this field.

NDN congestion control based on fuzzy comprehensive evaluation algorithm

The congestion control algorithm of the named data network is not accurate in obtaining the congestion status, and the research is not carried out in time, and a congestion control strategy based on the fuzzy comprehensive evaluation algorithm is proposed. This strategy uses the fuzzy comprehensive evaluation algorithm to calculate and analyze the above two network parameters to obtain the network congestion state by detecting the buffer queue length of the network intermediate node and the actual and predicted round-trip time ratio. In order to refine the degree of network congestion, a variety of congestion is designed. The feedback signal uses the existing NACK feedback mechanism of the NDN network to send a congestion signal to the downstream node, and the downstream node adaptively adjusts the interest packet sending rate according to the congestion signal to achieve the purpose of reducing network congestion. In the NDN-SIM simulator, this algorithm is compared and analyzed with mainstream algorithms, and it is confirmed that this strategy can make full use of network resources and has higher transmission efficiency.

Research and implementation of condition monitoring and evaluation for process switch of intelligent substation

There are some problems in the regular inspection of switch, such as lack of real-time, lack of maintenance and over maintenance, this paper proposes a method for monitoring and evaluating the status of process layer intelligent switches . According to IEC61850 standard, the information model of switch is established to obtain the status information of the switch. The status information data is analyzed through the monitoring model of over-limit, synchronization, mutation and trend warning, and the status of switch is quantitatively evaluated by the fuzzy comprehensive evaluation algorithm. The example shows that this method can effectively evaluate the state of switch, which provides application technical support for state maintenance of process layer intelligent switches.