Fuzzy Judgment Research Articles

Production planning optimization with fuzzy analytic hierarchy process and genetic algorithm

Proper production planning is essential for improving productivity and lowering resource (material, energy, employees) related costs in the highly competitive business world. Dealing with the challenges of asymmetric setup times—where the time required to switch between manufacturing different products varies —makes this task much more difficult. Conventional planning techniques frequently ignore these articulations and produce sub-optimal schedules. This paper proposes a novel approach to tackle the following challenge: optimizing production planning using the Fuzzy Analytic Hierarchy Process (FAHP) with asymmetric setup times and Genetic Algorithm (GA). The proposed methodology involves a step-by-step process. The first stage defines key objectives: makespan, total waste cost, and maximum weighted tardiness. Decision-makers compare the relative importance of each criterion within its hierarchy level using fuzzy numbers. The consistency of these comparisons is assessed using fuzzy consistency ratio computations. At the same time, the overall priority weights for each production planning alternative are determined by summing fuzzy judgments across the hierarchy. In the second stage, the production plan is optimized using GA, considering sequence and lot size variables and asymmetric setup times, by applying the computed weights. The comparisons are performed using the proposed approach with the optimum solution.

Application Analysis of Fuzzy Language Based on Evolutionary Neural Network in Art Teaching

In order to improve the teaching effect of art teaching, the performance effect of fuzzy language in art teaching is studied. This paper analyzes the application of fuzzy language in art teaching, and evaluates its performance effect on this basis. After determining the application strategy of fuzzy language in art teaching, the evaluation index system is constructed. Evolutionary neural network is used to calculate the weight of evaluation index. Based on the evaluation index weight and fuzzy judgment matrix, the evaluation results of the performance effect of fuzzy language in art teaching are obtained. The experimental results show that the evaluation indicators selected by this method have high contribution and noise tolerance, and can accurately evaluate the performance effect of fuzzy language in art teaching, which proves that using fuzzy language in art teaching can effectively improve the quality of art teaching.

Efficient slicing scheme and cache optimization strategy for structured dependent tasks in intelligent transportation scenarios

The challenges posed by structured large-scale tasks to resource-sensitive intelligent transportation systems have been acknowledged, particularly regarding the need to reduce delay and energy consumption during the caching and offloading processes. To address these challenges and improve the quality of service for vehicular users, a cloud–edge-end collaboration caching strategy (CACCSC) based on structured task content awareness was proposed in this paper. The dependencies among task fragments were modeled through fuzzy judgment criteria. In addition, a system delay model, an energy consumption model, and an edge server load balancing model were developed, along with a multi-objective optimization model that integrates system delay, energy consumption, and edge server load balancing variance. To solve this multi-objective optimization problem, an adaptive multi-objective optimization algorithm (MDE-NSGA-III) was developed, which combines an enhanced version of the Differential Evolution algorithm with improvements to the NSGA-III algorithm. Finally, it has been demonstrated through simulation experiments that when the number of users in the system reaches 35, the system delay, energy consumption, and load balancing variance of the MDE-NSGA-III optimization scheme proposed in this paper are 6.1%, 6.6%, and 25% lower than those of the NSGA-III scheme, 15.8%, 10%, and 41.7% lower than those of the NSGA-II scheme, and 62.7%, 20.7%, and 8.3% lower than those of the PeEA scheme.

Evaluation of green governance of energy projects along the Belt and Road

PurposeThis study aims to enhance the assessment of green governance in energy projects along the Belt and Road, reduce the influence of fuzzy judgment, and construct a grey network analysis model from the perspective of Environmental, Social, and Governance (ESG).Design/methodology/approachThe ESG concept is used to establish an evaluation indicator system. The Analytic Network Process (ANP) and the Grey System Theory are applied sequentially to determine the green governance grade of energy projects, exemplified by an evaluation of five projects.FindingsThe Karot hydropower project has the best green governance status among the five projects and is of excellent grade. This is followed by the Hongfeng photovoltaic project, the De Aar wind power project, and the Yamal liquefied natural gas project, which are of good grade. The Lamu coal power station project has the worst green governance and is at a medium level.Practical implicationsThis study can assist Belt and Road energy projects in identifying their deficiencies and promoting sustainable development by providing a robust framework for green governance evaluation.Originality/valueThe indicator system developed in this study includes social and project governance aspects in addition to environmental performance, reflecting the comprehensive green governance status of projects. The combined use of ANP and grey system theory fully considers the mutual influence relationship between indicators and improves the objectivity of green governance grade judgment.

The weight fuzzy judgment method for the benchmarking sustainability of oil companies

The environmental, social, and economic challenges associated with the massive activities of the oil and gas industry require analysis and evaluation of companies' sustainability priorities. Evaluating the environmental performance of oil companies requires the application of strict mathematical tools and models that provide rigorous results. Multi-criteria decision-making (MCDM) is a rigorous tool that evaluates the performance and practices of oil and sustainable energy companies. However, classical multi-criteria decision analysis has problems related to inconsistency because of the subjective nature of pairwise comparisons. This study responded to the literature call by utilizing the weight fuzzy judgment method (WFJM) to determine the weight coefficients of criteria with zero consistency. Such a method employed criteria values and expert judgment for decision-making to create a bridge between the mathematical approach and the human approach. This study aims to develop a solid decision support system by evaluating and benchmarking 11 companies utilizing the fuzzy judgment method based on fuzzy theory and the VIekriterijumsko KOmpromisno Rangiranje (VIKOR) method to determine sustainability priorities for oil and gas companies. The oil companies’ criteria were efficiently weighted by the fuzzy judgment method, and the organizational capabilities represented the greatest weight value of 0.128, whilst the low-weight criteria were the high costs of technologies at 0.080. Besides, the benchmarking results for oil companies revealed that COM 8 was the best, whilst COM 11 was the worst. The fuzzy judgment technique is a unique approach to solving complicated decision-making problems, and its influence can be significant. Furthermore, this method can be applied in sectors other than energy, including banking, medical services, and engineering, where decision-making is not straightforward and requires a systematic approach.

Aspiration level-based non-dominated sorting genetic algorithm II & III to solve fuzzy multi-objective shortest path problem

The present article provides aspiration level-based non-dominated sorting genetic algorithm-II and III techniques for solving a fuzzy multi-objective shortest path problem utilizing an exponential membership function with a possibility distribution. Furthermore, in this study, using ?-level sets, fuzzy judgement was categorized for the decision maker to simultaneously optimize fuzzy objective functions scenarios as optimistic, most likely, and pessimistic. A numerical illustration is presented together with a data set to demonstrate the use of the suggested techniques. A comparison is performed between the suggested methodology and several other approaches. The sensitivity of the objective functions is also investigated using aspiration levels and shape parameters. The coverage is computed to assess the effectiveness of the proposed methods. This research concludes that the suggested approaches can manage fuzzy multi-objective shortest path problems competently and efficiently with a solid yield, allowing the decision maker to make a decision based on its aspiration level.

Slovak Existential Adverbs zavše, chvíľami, z času na čas on the Background of German (According to the Parallel Corpus)

The article analyzes the Slovak temporal adverbs zavše, chvíľami and z času na čas, belonging to a group with a common meaning “sometimes”, when a repetition of a certain situation is assumed, while the number of repetitions does not seem large to the speaker. These adverbs belong to the “near periphery” of the group, they are considered in a contrastive and comparative way, against the background of the German language, which has a long history of language contacts with the Slovak language. The analysis was carried out on the basis of the Slovak-German parallel corpus, which is part of the Slovak National Corpus. Due to the fact that translations from German into Slovak are mainly represented in this subcorpus, only German incentives of Slovak dialects are involved, and not vice versa; parallel translations from a third language are not involved. It is shown that for zavše the most frequent equivalent is manchmal, as well as bisweilen / zuweilen. For the adverb z času na čas, the main German equivalents are the adverbs of the und-group; as well as Von zeit zu zeit. Manchmal appears less often as an incentive – when the situation involves a clear fixation or can be potentially specified, also if its regularity is a consequence of some other situation. The largest number of equivalents, approximately comparable in number of occurrences, includes the Slovak adverb chvíľami, which can be the translation equivalent of lexemes manchmal, bisweilen / zuweilen, von zeit zu zeit, adverbs of und-group, also adverbs zeitweilig, zeitweise, zuzeiten, kurzzeitig, zwischenzeitlich, bald, and prepositional constructions with nouns Weile and Augenblick. The contexts of the appearance of chvíľami in translation are similar: this is a situation of direct observation in the narrative mode in the past; as well as a situation of “fuzzy judgment”, when it is difficult for the speaker to uniquely characterize the situation. All this allows us to speak about a certain ethnospecificity of the Slovak chvíľami.

A data-driven evaluation of student health impacts in teaching higher education physical education and health programs

Abstract In the field of physical education in the 21st century, with the rapid development of information technology, data-driven decision modeling has become an important means to improve the quality of teaching and promote the healthy development of students. The accurate assessment of students’ physical fitness levels and mental health is achieved through the use of fuzzy judgment and clustering algorithms in this paper. A data-driven platform for student health sports has been created by modeling sports users and sports and using the UB-CF recommendation algorithm, which includes personalized recommendations. The platform’s impact on students’ health is evaluated using a university as an example. The platform in this paper can provide students with different physical fitness courses with content that meets their own needs. After the experiment, students in the physical education and health course group saw a decrease in weight and hip circumference, respectively, by 2.59kg and 2.81cm, and their physical health improved further. And the platform presented in this paper can enhance the muscle fitness of students. In the experimental group, the standing long jump distance improved by about 10.25% compared with the preexperiment. The MAE of this paper’s method on the identification of psychological emotion “Depression” is only 0.296, which is much lower than the baseline method. Moreover, the method presented in this paper can accurately classify students according to their psychological problems. The purpose of this paper is to provide practical guidance for the innovative development of physical education in colleges and universities.

Evaluation of English Teaching Quality Based on Hierarchical Analysis and Fuzzy Decision Tree Algorithm

Abstract How to improve classroom teaching evaluation so that it can really play the role of guidance, motivation, and promotion of evaluation in the new classroom model is a problem that needs to be solved urgently. This paper first introduces the concepts of fuzzy hierarchical analysis and fuzzy comprehensive evaluation, defines the fuzzy judgment matrix, designs a multi-level fuzzy comprehensive judgment algorithm, and constructs a fuzzy hierarchical analysis-fuzzy comprehensive evaluation model. Then, the generalized fuzzy decision tree model is constructed to achieve a clearer and more effective hierarchical categorization of teaching quality evaluation indexes, and the teaching evaluation index system is established accordingly. Teaching quality evaluation is carried out in the English classrooms of three different teachers in a university, and it is found that the classification effect of this paper’s algorithm is better than that of other comparative algorithms in each evaluation index on the datasets FLAGS and BIRDS. In the university’s teaching quality evaluation validation for three English teachers, X, W, and Y, the comprehensive evaluation scores given by this paper’s method are 94.98, 85.92, and 73.32, respectively, which are in line with the actual teaching situation of the three teachers. This study provides new ideas and methods for reforming classroom teaching evaluation.

Application and Performance Evaluation of Industrial Internet Platform in Power Generation Equipment Industry

The development and application of the industrial Internet platform (IIP) has brought enterprises huge benefits, such as improving the efficiency of resource management and equipment maintenance, achieving the precipitation and reuse of industrial knowledge, and enhancing the development ability of industrial APPs, etc. Therefore, in order to accelerate the application of the IIP, promote the digital transformation of enterprises, and enhance the application effect of the IIP, it is necessary to evaluate the application level and performance of the enterprise IIP. In this paper, taking the IIP in the power generation equipment industry as the research object, the background, architecture, and implementation process of the platform is described, and an evaluation method is proposed. First, a third-level evaluation index system is proposed via reference analysis and the Delphi method from four dimensions—platform basic condition, platform technology capability, platform application service capability, and platform input–output capability—and a total of sixty-five bottom indexes are designed in particular. Then, the fuzzy analytic hierarchy process (FAHP) and particle swarm optimization (PSO) algorithm are used to determine the weights of indexes, where FAHP is used to construct a fuzzy judgment matrix and PSO is adopted to adjust the consistency of the fuzzy judgment matrix in the FAHP. Finally, through the weights of indexes and questionnaire scores, the evaluation results are obtained, and the application level and performance of the IIP in the power generation equipment industry is analyzed. Through analysis, the important indexes that have a significant influence on the evaluation are determined, and the weaknesses that need to be enhanced are also pointed out, which can guide enterprises to make targeted improvements on the IIP in the power generation equipment industry so as to ensure the sustainable development of the power generation equipment industry.

Optimization of Teacher Incentive Mechanism and Policy Supply in Rural China Based on Judgment Matrix

Abstract With the continuous development of artificial intelligence technology, rural education is crucial in Chinese education, and the problem of rural teachers’ incentive mechanisms directly affects the quality of rural education. Firstly, according to the incentive mechanism of rural teachers, quantitative and qualitative research on the incentive mechanism of teachers in rural areas using the fuzzy evaluation method is proposed. In the fuzzy judgment matrix, each level is determined based on the decomposition of the previous level, and the results of the previous level are determined based on the calculation results of the next level. Then, using the relevant motivation theory and questionnaires, the principal and teachers of the school were investigated to understand the current situation and main problems of the construction of teachers’ motivation mechanism in the junior high school of Un Dong Town, Duyun City. Using the fuzzy evaluation method to analyze the difference between the actual feeling and expected demand of teachers’ motivation, the result shows that the difference between salary and promotion is 1.22 and 1.19, which means that the difference between salary and promotion is bigger in the motivation mechanism of rural teachers, and we should focus on reforming the salary scheme and implementing the promotion training mechanism of rural teachers. This study confronts the problem of rural teachers’ incentive mechanism, which has good theoretical and practical guidance for improving education quality and so on.

Exploration and Practice of College English Reading Teaching Reform in the Context of Deep Learning

Abstract To improve the quality and effectiveness of learners’ English reading learning, this paper proposes a fuzzy hierarchical analysis method incorporating deviance entropy (DE-FAHP), which improves the differentiation quality of the fuzzy judgment matrix and enhances the accuracy of weight calculation of each influencing factor by introducing deviance entropy model. Finally, the comprehensive difficulty quantification model of English reading comprehension objective questions is determined to provide an efficient and accurate method for calculating the parameters of the subsequent English reading comprehension standardized question bank. Finally, this paper proposes a hybrid testing method that combines CAT’s online grouping technology with MST’s staged presentation of test questions to construct the English reading comprehension adaptive testing system ca-MST. Through system validity testing, students in the experimental class improved more significantly, with only question 20 in the experimental class scoring below 4.0, while most of the scores in the control class were below 4.0. The mean reading score of the experimental class was 76.31, with a standard deviation of 11.16, while the mean reading score of the control class was 69, with a standard deviation of 18.76. The comparison showed that the reading scores of the experimental class taught with the reading comprehension adaptive testing system were higher than those of the control class taught with the traditional model, and the differences within the class were smaller.

Application of Multi-Level Fuzzy Comprehensive Evaluation in the Pension Industry of Combination of Medical and Nursing in Heilongjiang Province

The development of pension service industry is the internal requirement of building a harmonious society and promoting the coordinated development of economy and society. Construction of evaluation index system of combination of medical and nursing. There are 6 primary indicators and 21 secondary indicators. By means of questionnaire, this paper investigates the satisfaction of the current medical and nursing industry in Heilongjiang Province, and establishes a fuzzy judgment matrix. The entropy method is used to determine the weight of each index, and the multi-level fuzzy evaluation model of the combination of medical care and pension industry in Heilongjiang Province is established. The comprehensive score was 78.65. It shows that the industry of the combination of medical care and pension in Heilongjiang Province is at the middle and upper level. Although people are very satisfied with the current pension industry, there is still room for improvement. Finally, according to the analysis of the results of the above model, some suggestions are put forward to effectively promote the development of the industry.

Retracted: Evaluation and Application of College English Mixed Flipping Classroom Teaching Quality Based on the Fuzzy Judgment Model

Retracted: Evaluation and Application of College English Mixed Flipping Classroom Teaching Quality Based on the Fuzzy Judgment Model

Analysis of the environmental resources value and enterprises economic benefits based on combination algorithm

Abstract To solve the problems of fuzziness, nonlinearity and complexity of economic factors and environmental factors in the evaluation of ecological economic benefits of enterprises are studied. Based on the theory of environmental-economic benefits (EEB), this paper defines the value of environmental resources and economic benefits of enterprises, and puts forward the indicators of environmental and economic benefits. The evaluation model of enterprise EEB based on the analytic hierarchy process and fuzzy set algorithm is constructed. By establishing the hierarchical structure model of index system, the intuitive fuzzy judgement matrix is obtained, and the final score of enterprise environmental benefits is calculated by consistency test and weight analysis. After verifying the model, the evaluation method of enterprise EEB proposed in this paper is accurate and reliable, which is helpful to deeply analyse the hidden order and adaptation mechanism of complex adaptation system of enterprise environmental management.

Hydropower Unit State Evaluation Model Based on AHP and Gaussian Threshold Improved Fuzzy Comprehensive Evaluation

Because a single monitoring index cannot fully reflect the overall operating status of the hydropower unit, a comprehensive state evaluation model for hydropower units based on the analytic hierarchy process (AHP) and the Gaussian threshold improved fuzzy evaluation is proposed. First, the unit equipment was divided into a hierarchical system, and a three-tier structure system (target layer-project layer-index layer) of the unit was constructed, and the weight of each component in the system was determined by the comprehensive weighting method. Secondly, according to the characteristics of the normal distribution of the historical health data of the unit, the upper and lower limits of the index were determined based on the Gaussian threshold principle, the real-time monitoring index degradation degree was calculated according to the index limit, and the degradation degree was applied to the fuzzy evaluation model to obtain the fuzzy judgment matrix. The result of assessment was divided into four sections: good, qualified, vigilant, and abnormal. Finally, combined with the unit hierarchical structure system, the weighted calculation of the fuzzy judgment matrix of each indicator, the overall fuzzy judgment matrix of the upper-level indicators of the unit was obtained, and the operating status of the unit was judged according to the matrix. Taking a real power plant unit as an example, the model was verified, and compared with other evaluation methods, the effectiveness and advantages of the proposed method were verified. In addition, the method proposed in this paper effectively solved the problems of index weighting and index limit determination in the existing model of unit condition evaluation.

Fuzzy Domination Graphs in Decision Support Tasks

In decision support tasks, one often has to deal with uncertainty due to fuzzy judgments of the decision maker or the expert. This paper proposes methods that allow you to rank the alternatives based on fuzzy evaluations. This is achieved by using fuzzy weighted summation, fuzzy implication, a computation graph showing the criteria, and a fuzzy dominance graph showing the alternatives. If the criteria have equal importance, then fuzzy graphs corresponding to the dominance of each of the criteria are used. An algorithm that is used for both the transition from fuzzy dominance graphs and the ranking of alternatives is proposed. This algorithm is based on the idea of constructing Kemeny medians or other concordant rankings at a given confidence level in the existence of corresponding arcs. Computational experiments have shown the performance of these approaches. It is reasonable to apply them in problems that require complex expert evaluations with a large number of alternatives and criteria.

Remote-sensing image data fusion processing technology based on multi-level fuzzy judgment

Remote sensing image technology is of great significance for dynamic management and monitoring of ground buildings. In order to improve the data fusion ability of remote sensing image of ground buildings, a data fusion method of remote sensing image of ground buildings based on multi-level fuzzy evaluation is proposed. This method constructs a remote sensing image acquisition model of ground buildings, and uses image enhancement methods to realize the gray information analysis and image enhancement of the remote sensing image rate of ground buildings. Finally, combining the remote sensing image data fusion method and the fuzzy region reconstruction method, it reconstructs the pixels of the dynamically changed ground buildings. The simulation results show that the remote sensing image data fusion accuracy of ground buildings is good, and the remote sensing feature extraction accuracy of ground buildings is high. The dynamic real-time monitoring of remote sensing image of ground buildings is realized.

Saaty’s consistency trapezoidal fuzzy extension and optimized fuzzy utility vector acquisition

Fuzzy extensions of Saaty’s consistency play an important role in developing fuzzy analytic hierarchy process based decision-making methods. This paper proposes formulas to calculate ratio-based increasing and decreasing spread indices and to obtain ratio-based indeterminacy indices of modal and support intervals for fuzzy judgments of trapezoidal fuzzy reciprocal preference matrices (TFRPMs). A transitivity equation with parametric fuzzy elements is introduced and combined with the existence of parameter values to define consistency of TFRPMs. To cope with the challenge of identifying the existence, computational formulas are developed to directly obtain values of parameters from the fuzzy judgments in a TFRPM, and an equivalent consistency concept is proposed for TFRPMs. Properties of consistent TFRPMs are presented and a logarithmic deviation based formula is provided to compute consistency indices of TFRPMs. A new framework of normalized vectors with trapezoidal fuzzy elements is introduced. A logarithmic goal programming model is established and transformed into a linear program for acquiring normalized trapezoidal fuzzy utility vectors from TFRPMs. An analytical solution is found for optimized trapezoidal fuzzy utility vectors of consistent TFRPMs. The developed models are validated by three numerical illustrations possessing comparative studies.

Sub-catchment-based urban flood risk assessment with a multi-index fuzzy evaluation approach: a case study of Jinjiang district, China

Urban flood risk assessment requires attention in inland areas with intensifying climate change and an increasing probability of extreme precipitation. This study describes the developments and testing of a sub-catchment-based multi-index fuzzy evaluation approach that can provide adaptation guidance for municipal decision-makers at a local level. We first built a comprehensive flood risk assessment system considering three categories: hazard, urban system, and social environment. The proposed evaluation system includes hybrid uncertain information that involves random indicator sources and hesitant fuzzy judgments from experts. The storm weather management model combined with geographic information system tools was then applied to obtain random indicators. Subsequently, hesitant fuzzy linguistic sets and the Euclidean distance method were adopted to solve the problem of uncertainty and vagueness from subjective hesitant information. Therefore, the aggregation method provides a beneficial way to assess flood risk in a hybrid uncertain environment. In addition, the proposed approach was applied to the Jinjiang district in an inland city in the P. R. of China. This supports efforts to prioritize locally tailored policies and practical measures for higher-risk sub-catchments within large urban systems.