Soft Computing Approaches in Chemistry

• Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
• Άλλοι συγγραφείς: Cartwright, Hugh M. (Επιμελητής έκδοσης, http://id.loc.gov/vocabulary/relators/edt), Sztandera, Les M. (Επιμελητής έκδοσης, http://id.loc.gov/vocabulary/relators/edt)
• Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
• Γλώσσα: English
• Έκδοση: Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2003.
• Έκδοση: 1st ed. 2003.
• Σειρά: Studies in Fuzziness and Soft Computing, 120
• Θέματα: Electronics.; Microelectronics.; Computational complexity.; Chemistry, Physical and theoretical.; System theory.; Vibration.; Dynamical systems.; Dynamics.; Electronics and Microelectronics, Instrumentation.; Complexity.; Theoretical and Computational Chemistry.; Systems Theory, Control.; Vibration, Dynamical Systems, Control.

This book brings together original work from a number of authors who have made significant contributions to the evolution and use of nonstandard computing methods in chemistry and pharmaceutical industry. The contributions to this book cover a wide range of applications of Soft Computing to the che...

Πίνακας περιεχομένων:

• Application of Evolutionary Algorithms to Combinatorial Library Design
• 1 Introduction
• 2 Overview of a Genetic Algorithm
• 3 De Novo Design
• 4 Combinatorial Synthesis
• 5 Combinatorial Library Design
• 6 Reactant Versus Product Based Library Design
• 7 Reactant-Based Combinatorial Library Design
• 8 Product-Based Combinatorial Library Design
• 9 Library-Based Designs
• 10 Designing Libraries on Multiple Properties
• 11 Conclusion
• References
• Clustering of Large Data Sets in the Life Sciences
• 1 Introduction
• 2 The Grouping Problem
• 3 Unsupervised Algorithms
• 4 Supervised Algorithms
• 5 Evaluation of Clustering Results
• 6 Interpretation of Clustering Results
• 7 Conclusion
• References
• Application of a Genetic Algorithm to the refinement of complex Mössbauer Spectra
• 1 Introduction
• 2 Theoretical
• 3 Experimental
• 4 Results
• 5 Discussion
• 6 Conclusions
• References
• Soft Computing, Molecular Orbital, and Functional Theory in the Design of Safe Chemicals
• 1 Introduction
• 2 Computational Methods
• 3 Neural Network Approach
• 4 Feed-Forward Neural Network Architecture
• 5 Azo Dye Database
• 6 Concluding Remarks
• Acknowledgement
• References
• Fuzzy Logic and Fuzzy Classification Techniques
• 1 Introduction
• 2 Fuzzy Sets
• 3 Case Studies of Fuzzy Classification Techniques
• 4 Conclusion
• References
• Further Reading
• Application of Artificial Neural Networks, Fuzzy Neural Networks, and Genetic Algorithms to Biochemical Engineering
• 1 Introduction
• 2 Application of Fuzzy Reasoning to the Temperature Control of the Sake Mashing Process
• 3 Conclusion
• Acknowledgements
• References
• Genetic Algorithms for the Geometry Optimization of Clusters and Nanoparticles
• 1 Introduction: Clusters and Cluster Modeling
• 2 Overview of Applications of GAs for Cluster Geometry Optimization
• 3 The Birmingham Cluster Genetic Algorithm Program
• 4 Applications of the Birmingham Cluster Genetic Algorithm Program
• 5 New Techniques
• 6 Concluding Remarks and Future Directions
• Acknowledgements
• References
• Real-Time Monitoring of Environmental Pollutants in the Workplace Using Neural Networks and FTIR Spectroscopy
• 1 Introduction
• 2 FTIR in the Detection of Pollutants
• 3 The Limitations of FTIR Spectra
• 4 Potential Advantages of Neural Network Analysis of IR Spectra
• 5 Application of the Neural Network to IR Spectral Recognition
• 6 Spectral Interpretation Using the Neural Network
• 7 Factors Influencing Network Performance
• 8 Comparison of Two and Three Layer Networks for Spectral Recognition
• 9 A Network for Analysis of the Spectrum of a Mixture of Two Compounds
• 10 Networks for Spectral Recognition and TLV Determination
• 11 Networks for Quantitative Spectral Analysis
• References
• Genetic Algorithm Evolution of Fuzzy Production Rules for the On-line Control of Phenol-Formaldehyde Resin Plants
• 1 Introduction
• 2 Resin Chemistry and Modelling
• 3 Simulation of Chemical Reactions
• 4 Model Comparison
• 5 Automated Control in Industrial Systems
• 6 Program Development
• 7 Comment
• References
• A Novel Approach to QSPR/QSAR Based on Neural Networks for Structures
• 1 Introduction
• 2 Recursive Neural Networks in QSPR/QSAR
• 3 Representational Issues
• 4 QSPR Analysis of Alkanes
• 5 QSAR Analysis of Benzodiazepines
• 6 Discussion
• 7 Conclusions
• References
• A Appendix
• Hybrid Modeling of Kinetics for Methanol Synthesis
• 1 Introduction
• 2 Neural Networks
• 3 Hybrid Modeling
• 4 Feature Selection
• 5 Modeling of Methanol Synthesis Kinetics
• 6 Conclusions
• A Appendix - Analytical Model of Methanol synthesis kinetics
• Acknowledgements
• References
• About the Editors
• List of Contributors.