Fuzzy methods for assessment and decision making

• Verfasst von: Voskoglou, Michael [VerfasserIn]
• Titel: Fuzzy methods for assessment and decision making
• Verf.angabe: Michael Gr. Voskoglou
• Verlagsort: San Diego
• Verlag: Elsevier Science & Technology
• Jahr: 2024
• Umfang: 1 online resource
• Fussnoten: Includes bibliographical references and index
• ISBN: 978-0-443-23733-1
• ISBN: 0-443-23733-6
• Datenträger: Online-Ressource
• Sprache: eng
• Bibliogr. Hinweis: Erscheint auch als : Druck-Ausgabe
• K10plus-PPN: 1910510521
• K10plus-PPN:
  Universitätsbibliothek
• Lokale URL UB: Zum Volltext
• Lokale URL UB: Bibliothek der Medizinischen Fakultät Mannheim der Universität Heidelberg
• Bibliothek/Idn: UW / m4629557784
• Lokale URL Inst.: Zum Volltext

Abstract

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.