Fuzzy Hierarchical Analysis Research Articles

Exploring the Construction of College Think Tank and Cultivation of Innovative Talents Based on Big Data Analysis

Abstract This paper combines the nine-factor model with the construction of university think tanks, establishes the strategic positioning of university think tanks, analyzes the methods and measures of cultivating leading talents and innovative talents in university think tanks and classifies the influence of university think tanks into decision-making influence, elite influence and popular influence. Based on the analysis of big data and concerning the fuzzy hierarchical analysis method, the evaluation model of information service quality of university think tanks has been established. The evaluation indexes of the information platform of university think tanks are divided into four indexes: service resources, service content, webpage technology, and service effect. According to the constructed evaluation indexes, two-by-two comparisons are made between each index to obtain the score of the importance of each index. Based on fuzzy mathematics, the qualitative evaluation can be transformed into quantitative evaluation according to the principle of affiliation degree to arrive at the evaluation grade of the information platform capacity of university think tanks and innovative talents.

Design of teaching aids in STEAM education and fuzzy hierarchical analysis of their educational effect

Focusing on problem-based learning (PBL) and the multi-disciplinary teaching of science, technology, engineering, arts, and mathematics (STEAM), we developed the evaluation tool of teaching aids in STEAM education to help students practice creative thinking and solution-finding. The fuzzy theory and the analytical hierarchy process were integrated for the evaluation of the acceptance of using robots in STEAM education. The fuzzy analytical hierarchy process (FAHP) was developed with the help of experts in education and industry who defined the goal, criteria, and alternatives (factors) of using teaching aids in STEAM education. FAHP was applied to the evaluation of three robots designed for STEAM education in this study. The result of the evaluation showed that the use of the designed robots in STEAM education was important in five criteria (structure, function, economy, aesthetic, and creativity). Among the alternatives, logic, creativity, simpleness, Avant-garde, and innovation were important for robots to be used for STEAM education. This indicated that artistic elements were important in the integration of them in STEAM education. The developed FAHP and questionnaire were useful in evaluating the acceptance of teaching aids in STEAM education. For the evaluation of the use of other teaching aids, the result of this study provides a basis and a reference for how teaching aids can be used for STEAM education.

Enhanced Presence Evaluation in Virtual Reality Feedback System with TOPSIS Model

Researcher has been trying to optimize the method for evaluating presence in virtual reality (VR) to address variability and uncertainty in quick evaluations using questionnaires. We recommend using the Technique for Order Performance by Similarity to Ideal Solution (TOPSIS) model to calculated the iGroup Presence Questionnaire to measure users’ overall presence in VR prototyping, instead of the weighted sum approach. The effects of two presence factors (scene density and motion trajectory technology) on a self-developed VR swimming virtual system were tested using the TOPSIS model with 20 participants each 12 tasks in a user experiment. The results were compared using two different weighting methods, fuzzy hierarchical analysis and uniform weighting methods. TOPSIS had a narrower range of data within the 95% confidence interval and a significantly lower coefficient of variation (CV). This indicates enhanced precision in evaluating presence and can be used to compare different technique setting of virtual systems.

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.

Research on the cultivation path of craftsmanship in university education based on fuzzy hierarchical analysis

Abstract This paper firstly explores the evaluation method of the level of cultivation of craftsmanship in colleges and universities and decomposes the problem to be analyzed into each component element that affects its goal by using the fuzzy hierarchical evaluation method. The hierarchical structure analysis model is established, and the upper influence factors of each layer are used as the basic criteria to compare each influence factor of the program layer and the criterion layer with each other, and the fuzzy consistency matrix is constructed to determine the relative weights of each divided influence factor. Then, the current situation of the level of cultivation of craftsmanship in college education and the problems of the cultivation mechanism of craftsmanship in colleges and universities were analyzed, and suggestions for improvement were put forward. In terms of the existing problems, 70% of them think that the atmosphere of attaching importance to craftsmanship spirit is insufficient, 80% of them think that the teaching method of craftsmanship spirit is in a single way, and 86% of them think that the excavation of craftsmanship spirit is not deep. In terms of the recognition of craftsmanship spirit, “respecting teachers and respecting morality”, “being willing to devote”, “being rigorous and meticulous”, “inheriting tradition “ and “innovation and creation” are all around 60%, while “excellence”, “love for work”, and “endurance of loneliness” are all around 60%. The approval rate of the artisan spirit of “enduring loneliness” is between 70% and 75%. The research of this paper is of great significance to the cultivation of craftsmanship in universities.

Research on the cultivation mechanism of “double-creative” talents in ethnic regions with the integration of industry and education in the context of the Internet

Abstract In the context of the rapid development of the Internet and big data technology, it is both an opportunity and a challenge for cultivating “dual-innovation” talents in ethnic regions. This paper proposes a fuzzy hierarchical analysis-fuzzy comprehensive evaluation model to study the cultivation mechanism of “dual-creative” talents in ethnic regions. The fuzzy hierarchical analysis-fuzzy comprehensive evaluation model consists of the evaluation system, a fuzzy comprehensive evaluation method, and a fuzzy hierarchical analysis. Then, based on the characteristics of fuzzy hierarchical analysis, the factors are organized and stratified to obtain a reasonable index set and build a hierarchical analysis structure. Using the fuzzy comprehensive evaluation method to analyze the school-enterprise cooperation in the integration of industry education in Tibetan higher vocational colleges, the results show that 55.4% of the students chose extremely unsatisfactory and unsatisfactory, indicating that they are not satisfied with the current communication status between the school and the internship enterprises, and another 28.6% of the students chose uncertainty full or unsatisfactory. This study explores the causes of the problems in the integration of industry-education personnel training from four levels: government, enterprises, society, and schools, and proposes guiding reference values for the integration of industry-education personnel training in Tibetan higher education institutions.

Problem identification and solution of voice change phenomenon in vocal singing based on the AHP method

Abstract The key points and difficulties in vocal singing are problem identification and clever transition in the voice change area. In this paper, by establishing the hierarchical structure model of the hierarchical analysis method, we compare the degree of importance of elements at different levels and the same level based on the judgment matrix to establish the weight vector and test the consistency of the judgment matrix. At the same time, for the problem that the hierarchical analysis method is not strongly targeted, the fuzzy comprehensive evaluation method is proposed for optimization, and then the fuzzy hierarchical analysis method is used to analyze the sound change phenomenon from the three primary indicators of breathing rhythm, resonance effect and sound representation and the related secondary indicators. The evaluation scores of the breathing rhythm control level were 7.83% and 13.77% lower than those of the professional level and master level, respectively; the evaluation scores of resonance effect were 10.70% and 13.37% lower than those of the professional level and master level, respectively; the evaluation scores of sound representation level were 9.26% and 14.32% lower than those of professional level and master level, respectively. The research based on hierarchical analysis can analyze the phenomenon of voice change in the process of vocal singing from a quantitative perspective, give scientific guidance to the practice of vocal singing, and help the development and prosperity of vocal singing art.

Retracted: Construction and Analysis of Green Investment Risk Evaluation Index System Based on Information Entropy Fuzzy Hierarchical Analysis Model

Retracted: Construction and Analysis of Green Investment Risk Evaluation Index System Based on Information Entropy Fuzzy Hierarchical Analysis Model

Energy Saving and Emission Reduction Potential Evaluation of a Coal Mine Based on Fuzzy Hierarchical Analysis

Due to the non-renewability of coal resources and the effect of excessive resource loss on the economic development of enterprises forming a constraint, breakthroughs in high energy consumption to achieve energy saving and emission reduction in coal mines represent an important way to promote the development of coal enterprises. This paper takes the energy-saving work of the Wuyang coal mine, which is very representative of China’s Shanxi Province, as an example, and uses hierarchical analysis to establish an assessment system for energy conservation and emission reduction in coal mines. We adopted on-site research, expert scoring, and project guidance to divide the factors affecting energy conservation and emission reduction in the Wuyang coal mine into 24 categories, and we then used fuzzy mathematical calculations to assess potential, which is of better practicability. The study shows that the grade of energy saving and emission reduction in the Wuyang coal mine is of a medium level, and the potential of energy saving and emission reduction is large. The main influencing factors are improving the recovery rate of refined coal, renovating pressurized filters, eliminating high-energy-consuming equipment, optimizing the parking process, replacing the flotation machine, and ensuring the intelligent management of power metering. According to the relevant factors derived from the energy-saving and emission reduction work at the Wuyang coal mine for implementing the relevant measures, we provide a reference for the work of energy saving and emission reduction in mines in order to promote the sustainable development of the coal mining industry.

Financial risk assessment management of state-owned enterprises based on cloud accounting in the era of big data

Abstract To solve the financial risk problem of enterprise financing difficulties and large financing amounts in the era of big data, this paper constructs a financial risk assessment model and evaluates the indexes of enterprise financial risk by combining it with cloud accounting products. Firstly, we assign and determine the weights, use the evidence theory to develop the enterprise financial risk evaluation, and determine the weights of each risk evaluation index. Secondly, we set up a fuzzy evaluation language set, calculate the maximum value of the fuzzy rubric affiliation function for the risk indicators of state-owned enterprises under cloud accounting, pre-process the obtained data, determine the specific indicator weights with the help of fuzzy hierarchical analysis, and carry out consistency tests on them. Finally, the relative importance of each indicator is calculated among the model factors to obtain the overall risk score of cloud accounting enterprise finance. The experimental results show that the risk level measured according to the steps of the cloud accounting risk assessment system, the data confidentiality risk score is 76.14, the cloud accounting product risk is 85.96, the service risk is 72.88, and only one item is higher risk. This shows that the use of cloud accounting financial risk control measures can improve the quality of financial risk management of enterprises.

Presenting a Semi-quantitative Model Based on the Resiliency Engineering Management Commitment Index in Assessing the Level of Preparedness Against Emergency Situations of Hospitals in a Fuzzy Environment (Case Study: Selected Faraja Hospitals in 2021)

Background and Objective: The main index in resilience engineering is the management commitment index. This study implemented a semi-quantitative risk assessment method based on the fuzzy hierarchical analysis method for the management commitment index to evaluate the resilience level of two selected hospitals. Materials and Methods: First, evaluation tools were designed, and their validity was determined. They included a 17-question hierarchical analysis questionnaire, a four-question management commitment risk assessment form, and a two-question integrated management commitment risk assessment form with safety, health, and environment. They were then distributed at Al-Ghadir Hospital in Tabriz and Khatam Al-Anbia Hospital in Bandar Abbas (affiliated with Faraja) and analyzed with relevant statistical methods. Results: The evaluation of the fuzzy hierarchical analysis questionnaire showed that the level of resilience had increased from 15.25 in 2018 to 36.37 in 2019. Additionally, the levels of social readiness, sharing, and resilience risk were 0.97, 0.17, and 0.03 in Al-Ghadir Hospital and 0.96, 0.11, and 0.04 in Khatam Al-Anbia Hospital, respectively. Moreover, the cumulative readiness value of management commitment based on safety, health, and environment in these two hospitals was 0.81 and 0.74, respectively. Conclusion: Based on the results, it is suggested that the selected hospitals focus on the effective parameters introduced in the evaluation tools of this study to increase their resilience level.

Presenting a Semi-quantitative Model Based on the Resiliency Engineering Management Commitment Index in Assessing the Level of Preparedness Against Emergency Situations of Hospitals in a Fuzzy Environment (Case Study: Selected Faraja Hospitals in 2021)

Background and Objective: The main index in resilience engineering is the management commitment index. This study implemented a semi-quantitative risk assessment method based on the fuzzy hierarchical analysis method for the management commitment index to evaluate the resilience level of two selected hospitals. Materials and Methods: First, evaluation tools were designed, and their validity was determined. They included a 17-question hierarchical analysis questionnaire, a four-question management commitment risk assessment form, and a two-question integrated management commitment risk assessment form with safety, health, and environment. They were then distributed at Al-Ghadir Hospital in Tabriz and Khatam Al-Anbia Hospital in Bandar Abbas (affiliated with Faraja) and analyzed with relevant statistical methods. Results: The evaluation of the fuzzy hierarchical analysis questionnaire showed that the level of resilience had increased from 15.25 in 2018 to 36.37 in 2019. Additionally, the levels of social readiness, sharing, and resilience risk were 0.97, 0.17, and 0.03 in Al-Ghadir Hospital and 0.96, 0.11, and 0.04 in Khatam Al-Anbia Hospital, respectively. Moreover, the cumulative readiness value of management commitment based on safety, health, and environment in these two hospitals was 0.81 and 0.74, respectively. Conclusion: Based on the results, it is suggested that the selected hospitals focus on the effective parameters introduced in the evaluation tools of this study to increase their resilience level.

A quadratic fuzzy relative evaluation approach for the high-quality development of marine economy

The ocean plays a crucial role in human society’s survival and development. While China’s marine economy has grown rapidly in recent years, it has also led to serious problems inhibiting ecosystem sustainability. This paper proposes high-quality development of the marine economy and combines the improved entropy value method, fuzzy hierarchical analysis method (FAHP), and data envelopment analysis (DEA) method to establish a quadratic relative evaluation model. A two-layer comprehensive index framework with 19 indicators is built to measure various aspects of the marine economy, including innovation, coordination, green, openness, and sharing. Empirical analysis conducted on 11 coastal provinces in China using data mainly collected from the Chinese Statistical Yearbook reveals significant spatial patchiness in the high-quality development level of the marine economy. This discrepancy is largely due to differences in geographical locations, resources, and government policies. The study analyzes four benchmark provinces of high-quality development and summarizes their experiences. The paper concludes by providing suggestions and implications to support government decision-making.

Exploring the Impact of Annual Report Inquiries on Audit Risk - Based on the Perspective of Anchoring Effect

The assessment of material misstatement risk is a critical judgmental matter for CPAs, but the uncertainty and subjectivity of judgment lead to a qualitative description of risk evaluation. By sorting out the inquiry letters issued by stock exchanges to listed companies in recent years, constructing a material misstatement risk system using fault trees and quantifying them using fuzzy hierarchical synthesis analysis, this paper not only provides a new reference basis and new audit ideas for annual audits, but also helps CPAs to better identify and evaluate material misstatement risks and improve the effectiveness of audits during annual audits.

Intelligent analysis system of college students' employment and entrepreneurship situation: Big data and artificial intelligence-driven approach

This study proposes an analysis plan for college students' employment and entrepreneurship based on big data and artificial intelligence, aiming to provide an important basis for the development of employment guidance activities. To realize feature analysis and useful information extraction of large-scale text information data, this study adopts a big data mining algorithm based on fuzzy hierarchical clustering analysis and semantic similarity correlation feature extraction. The algorithm uses generalization mapping to construct a semantic concept tree, and a fuzzy analytic hierarchy process to judge the semantic similarity and relevance of big data. This study demonstrates the efficacy of a big data mining algorithm through experimental verification. Two public datasets were used to validate the proposed method. The experimental results revealed that the method could efficiently process and analyze large textual datasets, leading to superior data classification performance.

Water Quality Index Estimations Using Machine Learning Algorithms: A Case Study of Yazd-Ardakan Plain, Iran

Excessive population growth and high water demands have significantly increased water extractions from deep and semi-deep wells in the arid regions of Iran. This has negatively affected water quality in different areas. The Water Quality Index (WQI) is a suitable tool to assess such impacts. This study used WQI and the fuzzy hierarchical analysis process of the water quality index (FAHP-WQI) to investigate the water quality status of 96 deep agricultural wells in the Yazd-Ardakan Plain, Iran. Calculating the WQI is time-consuming, but estimating WQI is inevitable for water resources management. For this purpose, three Machine Learning (ML) algorithms, namely, Gene Expression Programming (GEP), M5P Model tree, and Multivariate Adaptive Regression Splines (MARS), were employed to predict WQI. Using Wilcox and Schoeller charts, water quality was also investigated for agricultural and drinking purposes. The results demonstrated that 75% and 33% of the study area have good quality, based on the WQI and FAHP-WQI methods, respectively. According to the results of the Wilcox chart, around 37.25% of the wells are in the C3S2 and C3S1 classes, which indicate poor water quality. Schoeller’s diagram placed the drinking water quality of the Yazd-Ardakan plain in acceptable, inadequate, and inappropriate categories. Afterwards, WQI, predicted by means of ML models, were compared on several statistical criteria. Finally, the comparative analysis revealed that MARS is slightly more accurate than the M5P model for estimating WQI.

Selecting Green Suppliers by Considering the Internet of Things and CMCDM Approach

Selecting the suppliers in a green supply chain (GSC) improves supply chain capabilities by considering environmental policies. On the other hand, considering the development of technology and intelligence of the Internet of Things (IoT) and their help to meet goals better, it is essential to study them in this area. So, it is crucial to identify the influential factors of the IoT in selecting a green supplier and find its most important criteria for further monitoring and control. This paper aims to illustrate the ability of four different combinatorial multi-criteria decision-making (CMCDM) techniques in determining the best supplier in the rubber GSC. The suppliers are weighted using the fuzzy hierarchical analysis (FAHP) method, then ranked using four methods: VIKOR, TOPSIS, ELECTERE, and WASPAS. Then, their ranks are compared with each other. Eventually, Spearman’s rank correlation was examined to compare CMCDM methods. The results indicate that there is a similar ranking between all four CMCDM methods. Finally, it was found the second supplier is the best alternative for rubber companies looking for environmentally friendly suppliers. Also, FAHP-ELECTERE and FAHP-WASPAS methods have a high correlation with each other. The developed method can help decision-makers to make prompt decisions with less environmental pollution, which helps to achieve sustainable performance in the entire supply chain.

Research on the innovation of model based on the cultivation of talents in higher vocational art and design

Abstract Art and design are creative activities humans engage in to achieve certain purposes. The multiple characteristics of art and design also put forward more requirements for developing higher education art and design education. In this paper, starting from the problem that the multiple characteristics of art and design make it difficult to evaluate the teaching quality, the FAHP-FCE evaluation system is proposed to score the quality of art and design talents training. Firstly, fuzzy hierarchical analysis (FAHP) is used to construct a judgment matrix to filter out evaluation indexes. Secondly, multi-level fuzzy comprehensive evaluation (FCE) is used to evaluate the evaluation indexes to obtain the score. Finally, conclusions were drawn by comparing the effectiveness of the two teaching models. The research results show that the effectiveness of the FAHP-FCE evaluation system-based art and design talent training teaching model is assessed as 83.47 points, which is 34.11% more effective, 23% more design ability, 31% more learning ability and 26% more hands-on ability than the traditional teaching model. The talent cultivation model in this paper enables students to master abstract design ability, helps to expand the field of creative thinking, enriches the language of modeling and artistic imagination, and improves comprehensive design ability and learning ability.

Evaluation of influencing parameters on the causes of occupational accidents in the construction industry using Fuzzy logic-AHP and Pareto theory (case study: Kurdistan province)

Introduction: Statistics show that occupational accidents in the construction industry are relatively high. Also, a significant percentage of these accidents in this industry leads to death. Therefore, in this study, the parameters affecting the causes of occupational accidents in the construction industry were evaluated using the combined method of Fuzzy logic-AHP and Pareto's theory in Kurdistan province, and management and engineering mitigation measures were determined.
 Methods and Materials: In this study, the effective parameters in the occurrence of accidents in the construction industry were identified and a questionnaire based on fuzzy hierarchical analysis was designed and distributed, which was completed by 83 occupational health and safety specialists in the Kurdistan province of Iran. The data analysis was done based on Fuzzy logic-AHP and Pareto theory.
 Results: In the evaluation of this study, out of the set of eight factors, unsafe conditions were found to be the most influential factor. Also, among the sub-factors of this index, the two parameters of lack of scaffolding and safety equipment for working at height and lack of protective fences in existing cliffs were the most important.
 Conclusion: Based on these results, it is suggested that to reduce the occurrence of accidents in this industry, control measures to create safe working conditions at height should be prioritized. Also, paying attention to the parameters determined by the Pareto theory in each factor can easily reduce more than 80% of the causes of occupational accidents in this industry.

Modeling the effect of emergency response on domino effects in the coal gasification process by fuzzy hierarchical analysis and Bayesian network.

Emergency response has an important impact on the mitigation of the domino effects. However, consequence analysis of the domino effect often ignores emergency response due to its complexity and uncertainty. In this paper, Fuzzy Analytic Hierarchy Process (FAHP) is adopted to evaluate the reliability of emergency response process. On this basis, using Bayesian Network (BN) model, the domino effect under the influence of emergency response is modeled. Based on the total duration of the above-mentioned emergency response process to determine the consequences of domino effect under the action of safety barriers. The application of the approach has been demonstrated by an illustrative case study. The results show that the probability of domino effect is reduced by an order of magnitude when active barriers, passive barriers and emergency response are considered together. This work can provide relevant basis for formulating safety protection measures in chemical process industry.