Decision consolidation: criteria weight determination using multiple preference formats
Decision Support Systems
International Journal of Approximate Reasoning
A causal analytical method for group decision-making under fuzzy environment
Expert Systems with Applications: An International Journal
A Systematic Fuzzy Decision-Making Process to Choose the Best Model Among a Set of Competing Models
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
Evaluating the integration of fuzzy logic into the student model of a web-based learning environment
Expert Systems with Applications: An International Journal
Review: Student modeling approaches: A literature review for the last decade
Expert Systems with Applications: An International Journal
Information Sciences: an International Journal
| Hi-index | 12.06 |
Members of university commissions decide on an especial sort of students' requests, based on various criteria. Since these decisions may seriously affect the students' future life, it is necessary to pay precise attention to the decision-making process. However, many causes like lack of mental readiness, impact of irrelevant factors, change in views and limitation in concentration power of the commission members plus some other undistinguishable facts can affect the decision process leading to many ruinous problems. The paper aims simulation of a decision-making process which is used by management or consulting teams in order to solve this usual problem. As an especial case study, it focuses on the decisions made by members of university commissions on an especial sort of students' requests, who have faced problems with their education. After analyzing the decision process, we have designed a hybrid expert system that can regenerate the process. In this system, the criteria shape a fuzzy rule base with linguistic variables and the membership functions are adjusted by experts through interviews and/or questionnaire. Indeed, it is a composition of a fuzzy MCDM and a fuzzy inference system (FIS). Moreover, to differentiate between the criteria, we have attributed weightings to the criteria, which are computed using a fuzzy AHP method. Results show that the system output error in comparison to the historical data is less than 5%, and it can resemble the council's behavior. This supporting system can be applied to generate consistent outputs that contribute in convergence and unification of the decisions, and hence preventing false aftermaths.