The second edition of this textbook provides a fully updated approach to fuzzy sets and systems that can model uncertainty - i.e., "type-2" fuzzy sets and systems. The author demonstrates how to overcome the limitations of classical fuzzy sets and systems, enabling a wide range of applications from time-series forecasting to knowledge mining to control. In this new edition, a bottom-up approach is presented that begins by introducing classical (type-1) fuzzy sets and systems, and then explains how they can be modified to handle uncertainty. The author covers fuzzy rule-based systems - from type-1 to interval type-2 to general type-2 - in one volume. For hands-on experience, the book provides information on accessing MatLab and Java software to complement the content. The book features a full suite of classroom material.
- Presents fully updated material on new breakthroughs in human-inspired rule-based techniques for handling real-world uncertainties;
- Allows those already familiar with type-1 fuzzy sets and systems to rapidly come up to speed to type-2 fuzzy sets and systems;
- Features complete classroom material including end-of-chapter exercises, a solutions manual, and three case studies -- forecasting of time series to knowledge mining from surveys and PID control.
Dieser Download kann aus rechtlichen Gründen nur mit Rechnungsadresse in A, B, BG, CY, CZ, D, DK, EW, E, FIN, F, GR, HR, H, IRL, I, LT, L, LR, M, NL, PL, P, R, S, SLO, SK ausgeliefert werden.