| Document Type
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BL
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| Record Number
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852029
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| Main Entry
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Ghaboussi, J.
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| Title & Author
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Soft computing in engineering /\ Jamshid Ghaboussi.
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| Publication Statement
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Boca Raton, FL :: CRC Press, Taylor & Francis Group,, [2018]
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| Page. NO
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1 online resource (xv, 204 pages)
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| ISBN
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0429470134
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: 0429892829
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: 1498745687
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: 9780429470134
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: 9780429892820
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: 9781498745680
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1498745679
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9781498745673
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| Bibliographies/Indexes
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Includes bibliographical references and index.
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| Contents
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Soft computing -- Neural networks -- Neural networks in computational mechanics -- Inverse problems in engineering -- Autoprogressive algorithm and self-learning simulation -- Evolutionary models -- Implicit redundant representation in genetic algorithm -- Inverse problem of engineering design.
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| Abstract
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"Soft computing methods such as neural networks and genetic algorithms draw on the problem solving strategies of the natural world which differ fundamentally from the mathematically-based computing methods normally used in engineering. Human brains are highly effective computers with capabilities far beyond those of the most sophisticated electronic computers. The 'soft computing methods they use can solve very difficult inverse problems based on reduction in disorder. This book outlines these methods and applies them to a range of difficult engineering problems, including applications in computational mechanics, earthquake engineering, and engineering design. Most of these are difficult inverse problems especially in engineering design and are treated in depth."--Provided by publisher.
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| Subject
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Engineering mathematics.
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Engineering-- Data processing.
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Soft computing.
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Engineering mathematics.
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Engineering-- Data processing.
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Soft computing.
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| Subject
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TECHNOLOGY ENGINEERING-- Engineering (General)
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| Subject
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TECHNOLOGY ENGINEERING-- Reference.
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| Dewey Classification
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620.00285/63
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| LC Classification
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TA345.G49 2018eb
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| Cover Title
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Biologically inspired soft computing in engineering
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