TY  - GEN
N2  - This book is the proceedings of the 3rd World Conference on Soft Computing (WCSC), which was held in San Antonio, TX, USA, on December 16-18, 2013. It presents start-of-the-art theory and applications of soft computing together with an in-depth discussion of current and future challenges in the field, providing readers with a 360 degree view on soft computing. Topics range from fuzzy sets, to fuzzy logic, fuzzy mathematics, neuro-fuzzy systems, fuzzy control, decision making in fuzzy environments, image processing and many more. The book is dedicated to Lotfi A. Zadeh, a renowned specialist in signal analysis and control systems research who proposed the idea of fuzzy sets, in which an element may have a partial membership, in the early 1960s, followed by the idea of fuzzy logic, in which a statement can be true only to a certain degree, with degrees described by numbers in the interval [0,1]. The performance of fuzzy systems can often be improved with the help of optimization techniques, e.g. evolutionary computation, and by endowing the corresponding system with the ability to learn, e.g. by combining fuzzy systems with neural networks. The resulting consortium of fuzzy, evolutionary, and neural techniques is known as soft computing and is the main focus of this book.
DO  - 10.1007/978-3-319-03674-8
DO  - doi
AB  - This book is the proceedings of the 3rd World Conference on Soft Computing (WCSC), which was held in San Antonio, TX, USA, on December 16-18, 2013. It presents start-of-the-art theory and applications of soft computing together with an in-depth discussion of current and future challenges in the field, providing readers with a 360 degree view on soft computing. Topics range from fuzzy sets, to fuzzy logic, fuzzy mathematics, neuro-fuzzy systems, fuzzy control, decision making in fuzzy environments, image processing and many more. The book is dedicated to Lotfi A. Zadeh, a renowned specialist in signal analysis and control systems research who proposed the idea of fuzzy sets, in which an element may have a partial membership, in the early 1960s, followed by the idea of fuzzy logic, in which a statement can be true only to a certain degree, with degrees described by numbers in the interval [0,1]. The performance of fuzzy systems can often be improved with the help of optimization techniques, e.g. evolutionary computation, and by endowing the corresponding system with the ability to learn, e.g. by combining fuzzy systems with neural networks. The resulting consortium of fuzzy, evolutionary, and neural techniques is known as soft computing and is the main focus of this book.
T1  - Advance trends in soft computingproceedings of WCSC 2013, December 16-18, San Antonio, Texas, USA /
AU  - Jamshidi, Mohammad,
AU  - Kreinovich, Vladik,
AU  - Kacprzyk, Janusz,
VL  - volume 312
CN  - SpringerLink
CN  - QA76.9.S63
N1  - International conference proceedings.
N1  - Includes author index.
ID  - 696279
KW  - Soft computing
KW  - Artificial intelligence
SN  - 9783319036748 
SN  - 3319036742 
TI  - Advance trends in soft computingproceedings of WCSC 2013, December 16-18, San Antonio, Texas, USA /
LK  - https://univsouthin.idm.oclc.org/login?url=http://dx.doi.org/10.1007/978-3-319-03674-8
UR  - https://univsouthin.idm.oclc.org/login?url=http://dx.doi.org/10.1007/978-3-319-03674-8
ER  -