Includes bibliographical references and index.
|Statement||L. Fortuna ... [et al.]|
|Series||Advanced textbooks in control and signal processing, Advanced textbooks in control and signal processing|
|Contributions||Fortuna, L. 1953-|
|LC Classifications||QA76.9.S63 S6334 2001|
|The Physical Object|
|Pagination||xii, 267 p. :|
|Number of Pages||267|
|LC Control Number||00046342|
Soft computing encompasses various computational methodologies, which, unlike conventional algorithms, are tolerant of imprecision, uncertainty, and partial truth. Soft computing technologies offer adaptability as a characteristic feature and thus permit the tracking of a problem through a changing by: Soft Computing: Neuro-Fuzzy and Genetic Algorithms and millions of other books are available for Amazon Kindle. Enter your mobile number or email address below and we'll send you a link to download the free Kindle App. Then you can start reading Kindle books on your smartphone, tablet, or computer - no Kindle device required/5(9). Offers an introduction to soft computing, a family consisting of many members, namely Genetic Algorithms (GAs), Fuzzy Logic (FL), Neural Networks (NNs) and others. In this book, the working cycle of a GA is explained in detail. It discusses the mechanisms of some specialized Gas with examples/5. The approach in this book is to provides an understanding of the soft computing field, to work through soft computing using examples, to integrate pseudo - 4/5(2).
The book concludes with the integration of genetic algorithms into the paradigm of soft computing methodologies, including several more industrial examples, implementation issues, and open problems and open problems related to intelligent control : $ This book provides a comprehensive knowledge of the fundamental concepts and techniques in soft computing, which is a burning topic of research now-a-days in the field of computational intelligence Author: Mrutyunjaya Panda. Soft Computing course 42 hours, lecture notes, slides in pdf format; Topics: Introduction, Neural network, Back propagation network, Associative memory, Adaptive resonance theory, Fuzzy set theory, Fuzzy systems, Genetic algorithms, Hybrid systems. Soft Computing encourages the integration of soft computing techniques and tools into both everyday and advanced applications. By linking the ideas and techniques of soft computing with other disciplines, the journal serves as a unifying platform that fosters comparisons, extensions, and new applications.
A hybrid technique, in fact, would deception. inherit all the advantages, but won't have the less desirable features of single soft computing componems. It has to possess a good learning capacicy, a better . This book gives an introduction to Soft Computing, which aims to exploit tolerance for imprecision, uncertainty, approximate reasoning, and partial truth in order to achieve close resemblance with human like decision making/5(34). This textbook provides a thorough introduction to the field of learning from experimental data and soft computing. Support vector machines (SVM) and neural networks (NN) are the mathematical structures, or models, that underlie learning, while fuzzy logic systems (FLS) enable us to embed structured human knowledge into workable algorithms. The book assumes that it is not only useful, but. Description: This book gives an introduction to Soft Computing, which aims to exploit tolerance for imprecision, uncertainty, approximate reasoning, and partial truth in order to achieve close resemblance with human like decision making.