TY - BOOK ID - 7537444 TI - Soft Computing Techniques in Engineering Applications AU - Patnaik, Srikanta. AU - Zhong, Baojiang. PY - 2014 SN - 3319046926 3319046934 PB - Cham : Springer International Publishing : Imprint: Springer, DB - UniCat KW - Engineering. KW - Computer vision. KW - Consciousness. KW - Computational Intelligence. KW - Image Processing and Computer Vision. KW - Cognitive Psychology. KW - Engineering KW - Soft computing KW - Engineering & Applied Sciences KW - Computer Science KW - Data processing KW - Machine vision KW - Vision, Computer KW - Construction KW - Image processing. KW - Computational intelligence. KW - Cognitive psychology. KW - Soft computing. KW - Data processing. KW - Electronic data processing KW - Cognitive computing KW - Computational intelligence KW - Apperception KW - Mind and body KW - Perception KW - Philosophy KW - Psychology KW - Spirit KW - Self KW - Artificial intelligence KW - Image processing KW - Pattern recognition systems KW - Industrial arts KW - Technology KW - Optical data processing. KW - Psychology, Cognitive KW - Cognitive science KW - Optical computing KW - Visual data processing KW - Bionics KW - Integrated optics KW - Photonics KW - Computers KW - Intelligence, Computational KW - Optical equipment UR - https://www.unicat.be/uniCat?func=search&query=sysid:7537444 AB - The Soft Computing techniques, which are based on the information processing of biological systems are now massively used in the area of pattern recognition, making prediction & planning, as well as acting on the environment. Ideally speaking, soft computing is not a subject of homogeneous concepts and techniques; rather, it is an amalgamation of distinct methods that confirms to its guiding principle. At present, the main aim of soft computing is to exploit the tolerance for imprecision and uncertainty to achieve tractability, robustness and low solutions cost. The principal constituents of soft computing techniques are probabilistic reasoning, fuzzy logic, neuro-computing, genetic algorithms, belief networks, chaotic systems, as well as learning theory. This book covers contributions from various authors to demonstrate the use of soft computing techniques in various applications of engineering. . ER -