https://publish.thescienceinsight.com/index.php/ijgs <h2>Why to publish in IJGS?</h2> <p><em>International Journal of Grey Systems</em> is the first American journal devoted to grey system theory and its application. It is published bi-annually in English in both print and online versions. IJGS publishes novel research involving Grey System Theory and related concepts. It is devoted to the international advancement of the theory and application of grey systems and uncertainty analysis. It seeks to nurture professional communication between scientists and practitioners who are interested in the theory and application of Grey System Theory. IJGS is an open access double-blind peer-reviewed journal, published by the <a href="https://thescienceinsight.com/">Science Insight</a> (USA) bi-annually. </p> Science Insight en-US International Journal of Grey Systems 2767-6412 <p>Creative Commons Non Commercial CC BY-NC: The work is distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 License which permits non-commercial use, reproduction and distribution of the work without further permission provided the original work is properly attributed.</p> <p> </p> https://publish.thescienceinsight.com/index.php/ijgs/article/view/93 <p>Aiming to address the issues of traditional student evaluation methods, which tend to be overly subjective and overlook the intrinsic data structure, this paper introduces a novel grey fuzzy clustering model named the grey entropy game-weighted fuzzy c-means (GEG-WFCM) model. Firstly, subjective weights are calculated using the subjective-objective relationship analysis method, while objective weights are determined through the entropy weight method. Then, a comprehensive approach is adopted, leveraging game theory to calculate the final weights. Based on these comprehensive weights, the relative grey correlation coefficient and fuzzy weighted c-mean algorithm are incorporated to yield the ultimate evaluation results. The proposed model was applied to evaluate student performance, and the experiments show that it can obtain scientific and reasonable results. The model not only acknowledges the expertise of experts but also respects the objectivity of the data, thus circumventing the limitations of purely subjective judgments, and surpassing traditional evaluation methods.</p> <p> </p> Yi Yang Caixia Liu Wanli Xie Copyright (c) 2024 Science Insight https://creativecommons.org/licenses/by-nc/4.0 2024-06-30 2024-06-30 4 1 11 22 10.52812/ijgs.93 https://publish.thescienceinsight.com/index.php/ijgs/article/view/88 <p>Decision Making (DM) is one of the most important components of human cognition. In particular, the Multiple-Criteria DM (MCDM), is a composite form of DM evaluating options with conflicting goals and choosing the best solution among the existing ones. Following the fuzzy DM criterion of Bellman and Zadeh in 1970, several other methods have been developed by other researchers for DM in fuzzy environments. Here we present a parametric, MCDM method utilizing grey numbers as tools. This method improves an earlier approach of Maji and colleagues in 2002, who used the tabular representation of a soft set as a tool for parametric MCDM in a fuzzy environment. The method is also extended to cover cases of weighted DM and suitable examples are presented illustrating our results.</p> <p> </p> Michael Gr. Voskoglou Copyright (c) 2024 Science Insight https://creativecommons.org/licenses/by-nc/4.0 2024-06-30 2024-06-30 4 1 5 10 10.52812/ijgs.88