Fuzzy Comprehensive Evaluation Model Research Articles

Study on Supply Shain Financing Scheme of A Vietnamese Coffee Company in China

This paper takes G7 Coffee, a Vietnamese coffee company, as an example to design a supply chain financing scheme suitable for the company. First of all, on the basis of explaining the concept of supply chain, supply chain financing and other related concepts, supply chain management theory, supply chain financing model, fuzzy comprehensive evaluation model and other theoretical foundations, based on the financing situation of a Vietnamese coffee company G7 coffee in China, combined with the financing problems of the company and the company's capital needs, The feasibility of supply chain financing of G7 Coffee in China for a Vietnamese coffee company is proposed. Secondly, this paper introduces the evaluation method of supply chain financing scheme of G7 Coffee in China of a Vietnamese coffee company. Finally, on the basis of clear objectives and principles of financing scheme design, an evaluation system of supply chain financing mode of a Vietnamese coffee company based on AHP is constructed. The applicability of accounts receivable supply chain financing, inventory supply chain financing and prepayment supply chain financing adopted by the company is further analyzed by fuzzy comprehensive evaluation method. The fuzzy comprehensive evaluation results show that The accounts receivable financing model is the best financing model for the supply chain financing of G7 Coffee in China of a Vietnamese coffee company. In order to ensure the smooth implementation of the supply chain financing plan of a Vietnamese coffee company G7 Coffee in China, this paper proposes to strengthen the guarantee from three aspects: financial system, credit management and risk control.

Optimizing organic fertilization towards sustainable vegetable production evaluated by long-term field measurement and multi-level fuzzy comprehensive model

Precision and efficient management of organic substitution fertilization is crucial in balancing soil health, environmental risks, and economic benefits for intensive crop cultivation. However, effectively determining the optimal organic substitution ratio in vegetable production remains uncertain and still relatively unexplored. We conducted a five-year vegetable field experiment and established four nitrogen-equivalent fertilization treatments: mineral fertilizer alone, and organic fertilizer substituting a quarter, half, and entirety of the mineral nitrogen. Employing a specialized multi-level fuzzy comprehensive evaluation model, our study assessed impacts of different organic substitution ratios on soil qualities, microbial diversity, vegetable yield and quality, environmental risks, and economic benefits in sustainable vegetable production of eastern China. Our results showed that the 50% organic substitution was optimal, significantly improving soil qualities and microbial characteristics, particularly in the topsoil layer. Compared to the control, this approach significantly reduced methane by 6.6–48.3%, nitrous oxide by 49.5–79.1%, and nitric oxide by 36.5–50.0%, while enhancing vegetable yield by 16.0–28.3% and its five-year average stability as well as quality as evidenced by increased protein, soluble sugar, and vitamin C contents. Economic analysis revealed that while it maximized environmental benefits, complete organic substitution did not consistently yield positive economic returns. In contrast, a 50% substitution ratio was identified as the most economically viable, representing a sustainable compromise that balances environmental health with economic feasibility. Further modeling analysis indicated an optimal comprehensive range between 42.9% and 64.5% for achieving the best balance of multiple objectives in vegetable fields. The study underscores the intricate organic substitution effects on intensive vegetable production, highlighting the necessity for tailored organic substitution strategies that integrate environmental sustainability with agricultural productivity and economic practicality.

Shortest Hamiltonian circuit algorithm for complex environments

Simply taking into account the static path length is insufficient to compute the shortest Hamiltonian circuit in complicated situations. To incorporate the influence of many factors on the shortest Hamiltonian circuit, this paper introduces a multi-objective fuzzy comprehensive evaluation model and quantitatively assesses the fuzzy factors. To better correctly reflect each influencing factor's importance in the problem-solving process, this paper also builds a hierarchical model to decide the weights assigned to each one. Finally, this paper adopts the state compression dynamic programming algorithm to solve the dynamic shortest Hamiltonian loop. In this study, an example analysis is also performed to confirm the algorithm's efficacy. Compared with the traditional algorithm, the algorithm designed in this paper comprehensively considers the influence of several factors when calculating the shortest Hamiltonian loop, and can more comprehensively evaluate the advantages and disadvantages of the path.

Research on training evaluation of new engineering talents in China local colleges under the background of regional economy

Under the regional economic background, local colleges have a crucial role in evaluating and researching the training of new engineering talents. With the continuous development of technology and the improvement of economic strength, training new engineering talents has become an important mission for local higher education institutions. This study aims to explore the evaluation methods and strategies for training new engineering talents in local colleges within the regional economic context. It proposes an evaluation system that selects and assesses indicators from five aspects: basic conditions, teaching process, practical proficiency, cultivation level of innovation ability, and cultivation effect. The results were obtained through a combination of the analytic hierarchy process and fuzzy comprehensive evaluation model and take two majors of A college as an example to evaluate and analyze the training effect of new engineering talents. Furthermore, this article presents valuable recommendations and countermeasures to enhance the training of new engineering talents in local colleges.

Quality evaluation of physical education in colleges and universities based on fuzzy logic

This study aims to evaluate the quality of physical education in colleges and universities by using the evaluation method based on fuzzy logic. First, summarize the basic concept of fuzzy logic and its application in the evaluation process. Then, a physical education quality evaluation index system covering teaching quality and students’ physical quality, teachers’ team construction, sports facilities and management is constructed. Then, the evaluation object and evaluation level are determined, and the specific evaluation results and ranking are calculated by fuzzy comprehensive evaluation model. In the empirical analysis, use the simulation data for model application and result analysis, and further find the problems existing in college physical education. Finally, in view of these problems, a series of improvement and optimization suggestions are put forward. This study shows that the evaluation method of physical education quality based on fuzzy logic can effectively reflect the diversity and complexity of education quality, and provide a practical evaluation tool for colleges and universities. At the same time, this study also provides a reference for other universities to help them better understand their own problems, so that they can take effective measures to improve. In addition, this method can be applied to other fields of education quality evaluation in the future, so as to provide more useful information for education reform and development.

A Comprehensive Evaluation of Shale Oil Reservoir Quality

To enhance the accuracy of the comprehensive evaluation of reservoir quality in shale oil fractured horizontal wells, the Pearson correlation analysis method was employed to study the correlations between geological parameters and their relationship with production. Through principal component analysis, the original factors were linearly combined into principal components with clear and specific physical meanings, aiming to eliminate correlations among factors. Furthermore, Gaussian membership functions were applied to delineate fuzzy levels, and the entropy weight method was used to determine the weights of principal components, establishing a fuzzy comprehensive evaluation model for reservoir quality. Without using principal component analysis, the correlation coefficient between production and evaluation results for the 40 wells in the Cangdong shale oil field was only 0.7609. However, after applying principal component analysis, the correlation coefficient increased to 0.9132. Field application demonstrated that the average prediction accuracy for the cumulative oil production per kilometer of fractured length over 12 months for the 10 applied wells was 91.8%. The proposed comprehensive evaluation method for reservoir quality can guide the assessment of reservoir quality in shale oil horizontal wells.

Ranking of components for reliability estimation of CBSS: an application of entropy weight fuzzy comprehensive evaluation model

Ranking of components for reliability estimation of CBSS: an application of entropy weight fuzzy comprehensive evaluation model

Process information optimization method based on process constituent elements model and polychromatic set theory

This research presents a novel model for optimizing process information in manufacturing steps through the utilization of Process Constituent Elements (PCE), with the aim of enhancing the effectiveness of product process information design. To achieve this objective, a systematic analysis is conducted on six dimensions: input, output, resources, value-adding activities, environment, and process control and inspection content. In addition, specific attributes of PCE are investigated, and an improved FP-growth algorithm is employed to extract the optimized structural expressions of typical PCE, thus determining specific expression requirements. The PCE and their attribute relationships are organized into modular mapping rules, resulting in an optimized representation structure based on a polychromatic set approach. The effectiveness of this approach is quantitatively assessed by developing a comprehensive quality indicator evaluation system for process information and using a fuzzy comprehensive evaluation model for analysis.

Comparison of prediction results of Dendrolimus punctatus larvae peak occurrence based on eight prediction models

AbstractIn order to clarify the prediction accuracy of eight models for predicting the peak occurrence of the first generation larvae of Dendrolimus punctatus and provide basis for the pest control, a catastrophe prediction model was established based on the peak occurrence of the first generation larvae of Dendrolimus punctatus in Qianshan City, Anhui Province from 1983 to 2016, and compared with other seven prediction models. Comparing the forecasting results in 2015 and 2016 with actual value and taking 1 head/plant as the error standard, the errors of multiple regression models with six factors as independent variables, namely, peak occurrence of pupae in overwintering generation, peak occurrence of eggs in the first generation, cumulative population in overwintering generation, peak occurrence of adults in overwintering generation, rainfall in early April and parasitic rate of Trichogrammatid in the first generation eggs of Dendrolimus punctatus, were 0.21 heads/plant and 0.23 heads/plant with accuracy rate of 100%. The errors of stepwise regression model with the same six factors were 0.23 head/plant and 0.29 head/plant. The prediction accuracy of artificial BP neural network model, Markov chain model, contingency table model, stationary time series model, and fuzzy comprehensive evaluation model was 100%, but variance period extrapolation model had an accuracy rate of 88%. The accuracy of catastrophe prediction model was related to the selection of catastrophe threshold. Comprehensive comparison of the above eight models, multiple regression, stepwise regression, artificial BP neural network, Markov chain model, stationary time series model, and catastrophe prediction model were more accurate.

Spatial supply-demand balance of health and failure consequences for urban sewer pipes

Sewer pipes health and failure consequences evaluation are vital to ensure the safety of urban sewer networks. Sewer pipes with low health and severe failure consequences should be the primary focus of daily maintenance and management for drainage authorities. Conversely, sewer pipes with high health and low failure consequences are temporarily not a primary concern, in order to reduce resource wastage within the constraints of limited economic and time resources. Thus, the scientific analysis of their relationships is deemed essential. This paper applies supply-demand balance theory to analyze the relationship. On the supply side, a health Fuzzy Comprehensive Evaluation model (HFCE) is proposed with weighted hierarchies established. On the demand side, a failure consequences FCE model (FFCE) is established. Each sewer pipe's supply-demand balance score is analyzed using matrix multiplication, highlighting two types of imbalanced pipes and sub-districts. Taking the Liangshui River Basin in Beijing as an example, the results show that the health evaluation can identify the spatial distribution of the health of sewer pipes, with low health levels V and IV accounting for 10.23 % and 4.43 %, respectively. The failure consequences evaluation can evaluate the spatial distribution of the severity of sewer pipe failure consequences, with high failure consequences levels V and IV respectively accounting for 10.97 % and 16.77 %. The supply-demand balance analysis identifies the proportion of the first and second types of imbalanced pipes, respectively 14.24 % and 6.80 %. This method, by analyzing the relationship of health and failure consequences, provides a decision-making basis for drainage authorities to prioritize sewer pipe operation management, repair, and maintenance.

English Teaching Quality Assessment Based on Fuzzy Comprehensive Evaluation Model

English Teaching Quality Assessment is a crucial aspect of evaluating and enhancing the effectiveness of English language education programs. To achieve a comprehensive understanding of teaching quality, a Fuzzy Comprehensive Evaluation Model is employed. This model combines qualitative and quantitative assessments, considering various factors such as teaching methods, student engagement, curriculum design, and instructor proficiency. Based on the multi-level model of Fuzzy mathematics, this paper designs a set of teaching Quality Assessment training suitable for English Teaching for Medical Students and applies it to teaching courses to improve their understanding of comprehensive functions and provide reference for future online teaching. In terms of curriculum structure, this paper uses Fuzzy analysis method and literature analysis method. Based on the literature, this paper discusses the training module, training theme, training content, training time and training mode. Summarize and organize the consultant's opinions, and finally formulate the training program. According to the teaching syllabus of comprehensive Quality Assessment student, teaching courseware was prepared, teachers conducted teaching demonstrations and recorded them as high-definition videos, and then cloud classroom teaching platform was built to teach community English. In terms of teaching practice, this subject took the tertiary medical institutions as the object, and investigated and evaluated the qualified primary care staff. Before training, the Fuzzy mathematics multi-level knowledge questionnaire, English Teaching Quality Assessment knowledge questionnaire, English Teaching Quality Assessment attitude, behavioral intention and self-efficacy scale were used to investigate the English Teaching. After completion, the methods were used to investigate English Teaching, and the different degrees of student effects were compared. Finally, a self-designed questionnaire was used to investigate English Teaching to understand the comprehensive evaluation of the satisfaction degree of student courses.

Hierarchical fuzzy comprehensive evaluation of prevention and control level of occupational hazards in coal mines

Objective: To establish an evaluation model for occupational hazard prevention and control levels in coal mines, to explore the combination of Analytic Hierarchy Process (AHP) and fuzzy comprehensive evaluation, to evaluate the overall situation of occupational hazard prevention and control in coal mines. Methods: In November 2021, Collect information of occupational hazards and their prevention and control status in 30 coal mines. AHP model was first constructed for the elements of occupational hazard prevention and control in coal mines. Then, the AHP and fuzzy comprehensive evaluation method was applied to comprehensively evaluate and grade the occupational hazard prevention and control in coal mines, using the principles of maximum membership and weighted average. Results: The hierarchical fuzzy comprehensive evaluation results for typical coal mine were basically consistent with its occupational hazard prevention and control situation. The dust prevention and control situation was good, the noise prevention and control situation is average, the occupational health monitoring situation was good, the occupational health management situation was average, and the overall level of occupational hazard prevention and control was good. Conclusion: The hierarchical fuzzy comprehensive evaluation model for occupational hazard prevention and control levels, combined with the principles of maximum membership and weighted average, can objectively evaluate and reflect the overall situation of occupational hazard prevention and control in coal mines.

A fuzzy comprehensive evaluation method based on the joint distribution dynamic membership degree for classification problems

In this study, we propose a new classification method by adopting some ideas originating from the fuzzy comprehensive evaluation (FCE). To make the FCE be a classifier, the class labels in classification problems are regarded as the evaluation remarks in the FCE, and the attributes in these two domains are regarded to be consistent. Then, to implement the FCE model B = W ∘ R and obtain an accurate classification result, on the one hand, a learning algorithm, which is based on the joint distribution of attribute values and is dynamic, is proposed to construct the fuzzy relational matrix R; on the other hand, equal weight is considered to constitute the weight vector W. Meanwhile, for a continuous dataset, the discretization method and the determination of the discretization class number corresponding to the proposed classifier are discussed. The proposed classifier not only innovatively extends the FCE to data mining but also has its own classification advantages, that is, it is easy to operate and has good interpretability. Finally, we perform some numerical experiments using publicly available datasets, and the experimental results demonstrate that the proposed classifier outperforms some existing classifiers.

Resilience assessment of metro stations based on AHP-PSO fuzzy combined empowerment method with baggage impact perspective

Fire accidents are one of the serious security threats facing the metro, and the accurate determination of the index system and weights for fire assessment in underground stations is the key to conducting fire hazard assessment. Among them, the type and quantity of baggage, which varies with the number of passengers, is an important factor affecting the fire hazard assessment. This study is based on the combination of subjective and objective AHP (Analytic Hierarchy Process) with the available Particle Swarm Optimisation algorithm PSO (Particle Swarm Optimization) and the perfect CRITIC (Criteria Importance Through Intercriteria Correlation) empowered fuzzy evaluation method on the metro station fire hazard toughness indicator system and its weights were determined, and a fuzzy comprehensive evaluation model of metro station safety toughness under the influence of baggage was constructed. The practical application proves that the method provides a new perspective for the fire risk assessment of underground stations, and also provides a theoretical basis for the prevention and control of mobile fire load hazards in underground stations.

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.

The Construction of English Translation Teaching System in Colleges and Universities Based on Cluster Search Algorithm

Abstract In the actual teaching of English translation, problems such as the disconnection of theory and practice and the insufficient perfection of the teaching system have emerged, which greatly affect the development of practical activities of English translation teaching in colleges and universities. This paper establishes the English translation teaching system based on the CIPP evaluation model, and to ensure the objectivity of the weights of evaluation indexes, the weights of the evaluation indexes are solved by cluster search algorithm, and the process of solving the index weights is optimized by using genetic algorithm. Taking ten universities in the university city of S province as the object of investigation, the corresponding questionnaires are designed to obtain the evaluation data, and the quality of English translation teaching is graded comprehensively evaluated, and analyzed through the fuzzy comprehensive evaluation model. The results show that: in the process of constructing the English translation teaching system in colleges and universities, the weight value of the teaching objectives reaches 0.2747, and the weight value of the implementation of the teaching links in the teaching process is the highest at 0.0493, and the use of the fuzzy comprehensive evaluation model can carry out a comprehensive evaluation of the quality of English translation teaching. The English translation teaching system of colleges and universities constructed based on CIPP evaluation model can help colleges and universities to find out the problems of English translation teaching and carry out innovative reforms in a targeted way, to improve the practical power of English translation teaching.

Research on the Development of College English Pedagogy System in Cross-cultural Perspective

Abstract Current college English programs at universities suffer from an inadequate teaching system and poor practical results, which hinder the effective development of students’ intercultural communication abilities and reduce their interest in learning the subject. This study integrates the output-oriented approach with blended teaching techniques to develop a college English teaching model. Utilizing University A as the research subject, we designed questionnaires and conducted teaching comparison experiments to evaluate the model’s effectiveness. The entropy value method calculated the weights of formative evaluation indices, while the fuzzy comprehensive evaluation model assessed the teaching quality. The results of the data analysis show that the reading character of students in class A under the blended teaching mode shows significant differences. The total score of reading level score is 21.07 points higher than that of students in class B with traditional teaching, and the speaking score rises by 3.468 points. The quality of college English teaching in University A was rated good, with a comprehensive score of 90.32 points using the fuzzy comprehensive evaluation model. The POA-based college English blended teaching model and formative evaluation system provide a new reference for innovating the college English teaching model in colleges and universities and boosting the intercultural communicative competence of college and university students.

Practical Exploration of Cultural Self-consciousness Enhancement of Civic Education for College Students in the Context of Deep Learning

Abstract Cultural self-awareness reflects a nation’s recognition of its own culture and other related values, which relies on a deep cultural foundation and is of great significance to national unity. This paper firstly analyzes the content and characteristics of cultural self-awareness, discusses the promotion role of college civic education on the cultivation and enhancement of college students’ cultural self-awareness, introduces the four-layer, four-ring model of educating people to innovate the form of civic education teaching and establishes a system of indicators for evaluating the effect of cultural self-awareness in civic education on the cultivation of people. Secondly, the subjective and objective weights of the evaluation indexes were solved by the AHP method and CRITIC method, respectively. The subjective and objective weights were combined by linear weighting method. Then, a fuzzy comprehensive evaluation model was established to comprehensively evaluate the effect of culturally conscious parenting in Civic and Political Education. Finally, five colleges and universities in a province were used as examples, and the research data was obtained through questionnaires and expert assignments to analyze the effect of culturally conscious parenting in each college and university. The results of the study show that in the effect of culturally conscious parenting on college students’ civic education, the weight of strengthening the innovation of cultural teaching content reaches 0.0726, while the weight value of promoting network culture innovation is only 0.0463, and the comprehensive evaluation score for the effect of cultural conscious parenting of civic education in college A is 9.884 points. The effect of cultural self-awareness in college students’ Civic and Political Education needs to rely on excellent culture, adopt richer teaching contents and forms, and encourage college students to internalize cultural knowledge and promote their cultural self-awareness.

Research on Regional Tea Tourism Product Development Strategy Combined with RMP Analysis

Abstract Tea culture tourism perfectly combines agricultural economic development and cultural tourism, a new trend in today’s tourism industry development. Based on the life cycle theory of tourist places and RMP theory, this paper comprehensively analyzes the three core dimensions of regional tea culture tourism product development: resources, market and products, using Province F as a case study. In the resource dimension, the combination assignment method containing preference information was used to determine the weights, and the fuzzy comprehensive evaluation model was applied to comprehensively evaluate the tea culture tourism resources. The market dimension analysis covers tea tourism’s development status and the characteristics of tourists’ travel behavior. For the product dimension, a quadrant diagram analysis was conducted using the IPA model by combining tourists’ perceived importance and satisfaction with the product. The study results show that Province F excels in tea tourism product development, with a comprehensive resource evaluation score of 90.756 points. Between 2010 and 2019, the tea tourism market received tourists at an average annual growth rate of 12.28%, reflecting the strong growth momentum of the market. Regarding product development, the average values of tourists’ perceived importance and satisfaction were 3.99 and 3.78, respectively, indicating that tourists’ overall satisfaction with tea tourism products is high. The study will help further enhance the attractiveness and competitiveness of tea tourism products and promote sustainable tourism development.

Analysis of Construction Quality Control Measures of Building Decoration Engineering Based on Big Data Technology

Abstract In the field of architectural decoration engineering, construction quality control is the main issue, which has a significant impact on project safety, cost and schedule. Under the background of the increasing maturity of big data technology, its application in the quality control of architectural decoration engineering has become a new trend in the industry, which is expected to improve quality management through technological innovation. This study analyzes the construction quality control measures of architectural decoration projects using big data technology to improve the efficiency and effectiveness of project quality management. The study utilizes PDCA and SDCA quality control theories, BIM technology, and extensive data analysis to fully monitor and assess the construction process of building decoration projects. The construction quality control mode using big data technology performs significantly better in improving project quality than traditional mode. The project’s second phase adopts the new model, and its construction quality score is higher than that of the first phase by more than 5 points on average, and the frequency of quality problems is reduced by 23%. A multi-layer fuzzy comprehensive evaluation model evaluates the quality control effect, and the construction quality control effect is rated as “excellent” with an affiliation value of 62.1%. The introduction of data technology significantly improves the efficiency and effectiveness of construction quality control in architectural decoration projects, and provides an effective management model for the industry.