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Название: Data-Driven Modelling with Fuzzy Sets: Embracing Uncertainty
Автор: Said Broumi, D. Nagarajan, Michael Gr. Voskoglou, S.A. Edalatpanah
Издательство: CRC Press
Серия: Intelligent Data‑Driven Systems and Artificial Intelligence
Год: 2024
Страниц: 348
Язык: английский
Формат: pdf (true)
Размер: 10.1 MB
Fuzzy sets have been widely used to represent imprecise and fuzzy information in the real world. Although they are effective in dealing with such data, their capability to handle incomplete and inconsistent information is restricted. Recently, several extensions of fuzzy sets have attracted attention because of their improved versatility. This book, entitled Data‑Driven Modelling with Fuzzy Sets: Embracing Uncertainty, explores theories and advancements in the field. It also examines the wide‑ranging applications of various extensions of fuzzy sets theory. Additionally, the book delves into the practical applications of fuzzy sets in knowledge management, including evaluating student learning abilities, assessing academic performance and screening technical articles. It is primarily written for Senior undergraduate and graduate students and academic researchers in the fields of electrical engineering, electronics and communication engineering, Computer Science and engineering.
Автор: Said Broumi, D. Nagarajan, Michael Gr. Voskoglou, S.A. Edalatpanah
Издательство: CRC Press
Серия: Intelligent Data‑Driven Systems and Artificial Intelligence
Год: 2024
Страниц: 348
Язык: английский
Формат: pdf (true)
Размер: 10.1 MB
Fuzzy sets have been widely used to represent imprecise and fuzzy information in the real world. Although they are effective in dealing with such data, their capability to handle incomplete and inconsistent information is restricted. Recently, several extensions of fuzzy sets have attracted attention because of their improved versatility. This book, entitled Data‑Driven Modelling with Fuzzy Sets: Embracing Uncertainty, explores theories and advancements in the field. It also examines the wide‑ranging applications of various extensions of fuzzy sets theory. Additionally, the book delves into the practical applications of fuzzy sets in knowledge management, including evaluating student learning abilities, assessing academic performance and screening technical articles. It is primarily written for Senior undergraduate and graduate students and academic researchers in the fields of electrical engineering, electronics and communication engineering, Computer Science and engineering.