Screen LibraryEngineering Applications of Soft Computing /
This book bridges the gap between Soft Computing techniques and their applications to complex engineering problems. In each chapter we endeavor to explain the basic ideas behind the proposed applications in an accessible format for readers who may not possess a background in some of the fields. Ther...
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| Main Authors: | |
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| Corporate Authors: | |
| Group Author: | ; |
| Published: |
Springer International Publishing : Imprint: Springer,
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| Publisher Address: | Cham : |
| Publication Dates: | 2017. |
| Literature type: | eBook |
| Language: | English |
| Series: |
Intelligent Systems Reference Library,
129 |
| Subjects: | |
| Online Access: |
http://dx.doi.org/10.1007/978-3-319-57813-2 |
| Summary: |
This book bridges the gap between Soft Computing techniques and their applications to complex engineering problems. In each chapter we endeavor to explain the basic ideas behind the proposed applications in an accessible format for readers who may not possess a background in some of the fields. Therefore, engineers or practitioners who are not familiar with Soft Computing methods will appreciate that the techniques discussed go beyond simple theoretical tools, since they have been adapted to solve significant problems that commonly arise in such areas. At the same time, the book will show members of the Soft Computing community how engineering problems are now being solved and handled with the help of intelligent approaches. Highlighting new applications and implementations of Soft Computing approaches in various engineering contexts, the book is divided into 12 chapters. Further, it has been structured so that each chapter can be read independently of the others. |
| Carrier Form: | 1 online resource(XV,258pages): illustrations. |
| ISBN: | 9783319578132 |
| Index Number: | Q342 |
| CLC: | TP18 |
| Contents: | Introduction -- Motion estimation algorithm using Block-matching and Harmony Search optimization -- Gravitational Search Algorithm applied to parameter identification for induction motors -- Color Segmentation using LVQ Neural Net-works -- Global Optimization using Opposition-Based Electromagnetism-like algorithm -- Multi-Threshold Segmentation using Learning Automata.-Real-time gaze control using Neurofuzzy prediction system -- Clonal Selection algorithm applied to Circle detection -- States of Matter Algorithm applied to Pattern Detection -- Artificial Bee Colony algorithm applied to Multi-threshold Segmentation -- Learning Automata applied to Planning Control -- Fuzzy-based System for Corner Detection. |