Soft Computing Approaches in Chemistry

This book PDF is perfect for those who love Technology & Engineering genre, written by Hugh M. Cartwright and published by Springer which was released on 06 December 2012 with total hardcover pages 327. You could read this book directly on your devices with pdf, epub and kindle format, check detail and related Soft Computing Approaches in Chemistry books below.

Soft Computing Approaches in Chemistry
Author : Hugh M. Cartwright
File Size : 50,9 Mb
Publisher : Springer
Language : English
Release Date : 06 December 2012
ISBN : 9783540362135
Pages : 327 pages
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Soft Computing Approaches in Chemistry by Hugh M. Cartwright Book PDF Summary

The contributions to this book cover a wide range of applications of Soft Computing to the chemical domain. The early roots of Soft Computing can be traced back to Lotfi Zadeh's work on soft data analysis [1] published in 1981. 'Soft Computing' itself became fully established about 10 years later, when the Berkeley Initiative in Soft Computing (SISC), an industrial liaison program, was put in place at the University of California - Berkeley. Soft Computing applications are characterized by their ability to: • approximate many different kinds of real-world systems; • tolerate imprecision, partial truth, and uncertainty; and • learn from their environment. Such characteristics commonly lead to a better ability to match reality than other approaches can provide, generating solutions of low cost, high robustness, and tractability. Zadeh has argued that soft computing provides a solid foundation for the conception, design, and application of intelligent systems employing its methodologies symbiotically rather than in isolation. There exists an implicit commitment to take advantage of the fusion of the various methodologies, since such a fusion can lead to combinations that may provide performance well beyond that offered by any single technique.

Soft Computing Approaches in Chemistry

The contributions to this book cover a wide range of applications of Soft Computing to the chemical domain. The early roots of Soft Computing can be traced back to Lotfi Zadeh's work on soft data analysis [1] published in 1981. 'Soft Computing' itself became fully established about 10 years later, when the Berkeley

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Soft Computing in Chemical and Physical Sciences

This book can be regarded as 'Soft computing for physicists and chemists self-taught'. It prepares the readers with a solid background of soft computing and how to adapt soft computing techniques to problem solving in physical and chemical research. Soft computing methods have been little explored by researchers in physical

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"This publication presents a series of practical applications of different Soft Computing techniques to real-world problems, showing the enormous potential of these techniques in solving problems"--Provided by publisher.

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An in-depth look at soft computing methods and their applications in the human sciences, such as the social and the behavioral sciences. Soft computing methods - including fuzzy systems, neural networks, evolutionary computing and probabilistic reasoning - are state-of-the-art methods in theory formation and model construction. The powerful application areas

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Hybrid Soft Computing Approaches

The book provides a platform for dealing with the flaws and failings of the soft computing paradigm through different manifestations. The different chapters highlight the necessity of the hybrid soft computing methodology in general with emphasis on several application perspectives in particular. Typical examples include (a) Study of Economic Load

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Download or read online Soft Computing Approach to Pattern Recognition and Image Processing written by Anonim, published by Unknown which was released on . Get Soft Computing Approach to Pattern Recognition and Image Processing Books now! Available in PDF, ePub and Kindle.

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Soft Computing Approach to Pattern Recognition and Image Processing

This volume provides a collection of sixteen articles containing review and new material. In a unified way, they describe the recent development of theories and methodologies in pattern recognition, image processing and vision using fuzzy logic, artificial neural networks, genetic algorithms, rough sets and wavelets with significant real life applications.

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