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Soft Computing Approaches in Chemistry

  • Book
  • © 2003

Overview

Editors:
  1. Hugh M. Cartwright

    1. Physical and Theoretical Chemistry, Oxford University, Oxford, UK

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  2. Les M. Sztandera

    1. CIS Department, Philadelphia University, Philadelphia, USA

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  • Invited papers with original work contributing to the evolution and use nonstandard computing methods in chemistry

Part of the book series: Studies in Fuzziness and Soft Computing (STUDFUZZ, volume 120)

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Table of contents (11 chapters)

  1. Front Matter

    Pages i-x
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  2. Application of Evolutionary Algorithms to Combinatorial Library Design

    • Valerie J. Gillet
    Pages 1-30

  3. Clustering of Large Data Sets in the Life Sciences

    • Ketan Patel, Hugh M. Cartwright
    Pages 31-49

  4. Application of a Genetic Algorithm to the refinement of complex Mössbauer spectra

    • Werner Lottermoser, Thomas Schell, Konrad Steiner
    Pages 51-66

  5. Soft Computing, Molecular Orbital, and Density Functional Theory in the Design of Safe Chemicals

    • Les Sztandera, Mendel Trachtman, Charles Bock, Janardhan Velga, Ashish Garg
    Pages 67-93

  6. Fuzzy logic and fuzzy classification techniques

    • S. M. Scott, W. T. O’Hare, Z. Ali
    Pages 95-134

  7. Application of Artificial Neural Networks, Fuzzy Neural Networks, and Genetic Algorithms to Biochemical Engineering

    • Taizo Hanai, Hiroyuki Honda, Takeshi Kobayashi
    Pages 135-159

  8. Genetic Algorithms for the Geometry Optimization of Clusters and Nanoparticles

    • Roy L. Johnston, Christopher Roberts
    Pages 161-204

  9. Real-time Monitoring of Environmental Pollutants in the Workplace Using Neural Networks and FTIR Spectroscopy

    • Hugh M. Cartwright, Andrew Porter
    Pages 205-236

  10. Genetic Algorithm Evolution of Fuzzy Production Rules for the On-line Control of Phenol-Formaldehyde Resin Plants

    • Hugh M. Cartwright, David Issott
    Pages 237-264

  11. A Novel Approach to QSPR/QSAR Based on Neural Networks for Structures

    • Anna Maria Bianucci, Alessio Micheli, Alessandro Sperduti, Antonina Starita
    Pages 265-296

  12. Hybrid modeling of kinetics for methanol synthesis

    • Primož Potočnik, Igor Grabec, Marko Šetinc, Janez Levec
    Pages 297-315

  13. Back Matter

    Pages 317-320
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Keywords

About this book

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.

Editors and Affiliations

  • Physical and Theoretical Chemistry, Oxford University, Oxford, UK

    Hugh M. Cartwright

  • CIS Department, Philadelphia University, Philadelphia, USA

    Les M. Sztandera

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