finelybook
Fuzzy Methods for Assessment and Decision Making
Author:Michael Gr. Voskoglou (Author)
Publisher finelybook 出版社:Morgan Kaufmann
Edition 版本:1st edition
Publication Date 出版日期:2024-10-22
Language 语言:English
Print length 页数:238pages
ISBN-10:0443237328
ISBN-13:9780443237324
Book Description
Fuzzy Methods for Assessment and Decision Making presents the assessment of learning and problem-solving skills with qualitative grades. These methods are outcomes of the author’s research work on the subject for more than 20 years. In particular, a hybrid assessment model uses the Center of Gravity (COG) defuzzification technique, closed real intervals (grey numbers), neutrosophic sets, and soft sets as tools. The book starts with the basic mathematical background that is needed for an understanding of its contents. The Rectangular Fuzzy Assessment Model (RFAM) of Subbotin and Voskoglou is presented next, the outcomes of which are compared to those of the GPA index.
The book presents innovative fuzzy assessment methods, enabling readers to assess the mean and quality performance of learning or problem-solving skills of a group of students when qualitative (linguistic) grades are used for this purpose. In the case of using linguistic grades for the assessment of a group’s skills, the classical method of calculating the mean value of the (numerical) grades cannot be applied. Also, no safe conclusions can be obtained on comparing the quality performance of two groups when the values of their GPA index are equal.
- Presents innovative, fuzzy assessment methods to enable readers to assess the mean and quality performance of learning
- Discusses fuzzy logic and techniques for decision-making in all domains
- Includes applications of fuzzy decision-making as a hybrid model using soft sets, grey numbers, and neutrosophic sets
Review
Presents the foundations of Fuzzy decision-making and assessment methods through a range of real-world applications
From the Back Cover
Assessment is a very important component of human activities because it helps in determining possible mistakes and in improving performance by preventing the repeat of such mistakes in future. Fuzzy Methods for Assessment and Decision Making presents the assessment of learning and problem-solving skills with qualitative grades. These methods are outcomes of the author’s research work on the subject for more than 20 years. In particular, a hybrid assessment model is developed using the Center of Gravity (COG) defuzzification technique, closed real intervals (grey numbers), neutrosophic sets and soft sets as tools. The book starts with the basic mathematical background which is needed for the understanding of its contents. The Rectangular Fuzzy Assessment Model (RFAM) of Subbotin and Voskoglou is presented next, the outcomes of which are compared to those of the GPA index. The necessary information follows regarding the learning and problem-solving processes, and the book then presents the hybrid assessment model. Dr. Voskoglou presents innovative fuzzy assessment methods, enabling the reader to assess the mean and quality performance of learning or problem-solving skills of a group of students when qualitative (linguistic) grades are used for this purpose. In the case of using linguistic grades for the assessment of a group’s skills, the classical method of calculating the mean value of the (numerical) grades cannot be applied. Also, no safe conclusions can be obtained on comparing the quality performance of two groups when the values of their GPA index are equal. The fuzzy assessment methods presented in this book solve these problems. Further, the use of neutrosophic sets enables readers to obtain safer results when there are doubts about the accuracy of the grades assigned to students, while the use of soft sets enables a parametric assessment of the group's overall performance. Furthermore, the book presents a variety of applications of Fuzzy assessment as well as the principles and application of fuzzy decision making, which is fundamental for a wide variety of AI, machine learning, computational intelligence, and knowledge engineering applications.
About the Author
Dr. Michael Gr. Voskoglou is an Emeritus Professor of Mathematical Sciences at the School of Technological Applications of the Graduate Technological Educational Institute, University of Patras, Greece. He has also taught at the Hellenic Open University, at the Mathematics Department of the University of Patras, and at the Schools of Primary and Secondary In-Service Teachers Training in Patras. As a visiting Professor he has taught postgraduate courses at the School of Management at the University of Warsaw, at the Department of Operational Mathematics of the University of Applied Sciences in Berlin, and at the Mathematics Department of the National Institute of Technology of Durgapur under a grant of the GIAN program of the Indian Government. He also worked for three years under sabbatical as a visiting researcher in the Institute of Mathematics and Informatics of the Bulgarian Academy of Sciences in Sofia. He has authored/edited 18 scientific books and has published more than 550 papers in reputed journals and proceedings of conferences of many countries all around the world, with about 1800 citations from other researchers. He is also reviewer of the American Mathematical Society and member of the Editorial Board or referee in many international mathematical journals. His research interests include Algebra, Fuzzy Sets, Markov Chains, Artificial Intelligence, and Mathematics Education.
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