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Neural networks in chemical reaction dynamics /
This monograph presents recent advances in neural network (NN) approaches and applications to chemical reaction dynamics. Topics covered include: (i) the development of ab initio potential-energy surfaces (PES) for complex multichannel systems using modified novelty sampling and feedforward NNs; (ii...
| Clasificación: | Libro Electrónico |
|---|---|
| Otros Autores: | |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
New York :
Oxford University Press,
©2012.
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| Temas: | |
| Acceso en línea: | Texto completo |
MARC
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| 245 | 0 | 0 | |a Neural networks in chemical reaction dynamics / |c Lionel M. Raff [and others]. |
| 260 | |a New York : |b Oxford University Press, |c ©2012. | ||
| 300 | |a 1 online resource (xiv, 283 pages) : |b illustrations | ||
| 336 | |a text |b txt |2 rdacontent | ||
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| 504 | |a Includes bibliographical references and index. | ||
| 588 | 0 | |a Print version record. | |
| 520 | |a This monograph presents recent advances in neural network (NN) approaches and applications to chemical reaction dynamics. Topics covered include: (i) the development of ab initio potential-energy surfaces (PES) for complex multichannel systems using modified novelty sampling and feedforward NNs; (ii) methods for sampling the configuration space of critical importance, such as trajectory and novelty sampling methods and gradient fitting methods; (iii) parametrization of interatomic potential functions using a genetic algorithm accelerated with a NN; (iv) parametrization of analytic interatomic. | ||
| 505 | 0 | |a Cover; Contents; Preface; Acronyms; 1. Fitting Potential-Energy Hypersurfaces; 1.1. Introduction; 1.2. Empirical and Semi-Empirical Potential Surfaces; 1.3. Ab Initio Potential-Energy Surfaces (PESs); 1.4. Other Fitting Methods for Potential-Energy Surfaces; 1.5. Neural Network (NN) Approach; 1.6. Essential Steps in a Molecular Dynamics Simulations; 1.7. Organization of the Monograph; 2. Overview of Some Non-Neural Network Methods for Fitting Ab Initio Potential-Energy Databases; 2.1. Introduction; 2.2. Moving Shepard Interpolation (MSI) Methods; 2.2.1. Required Input Data. | |
| 590 | |a ProQuest Ebook Central |b Ebook Central Academic Complete | ||
| 590 | |a eBooks on EBSCOhost |b EBSCO eBook Subscription Academic Collection - Worldwide | ||
| 650 | 0 | |a Chemical reactions |x Data processing. | |
| 650 | 0 | |a Neural networks (Computer science) | |
| 650 | 6 | |a Réseaux neuronaux (Informatique) | |
| 650 | 7 | |a SCIENCE |x Chemistry |x Physical & Theoretical. |2 bisacsh | |
| 650 | 7 | |a Chemical reactions |x Data processing |2 fast | |
| 650 | 7 | |a Neural networks (Computer science) |2 fast | |
| 700 | 1 | |a Raff, Lionel M. | |
| 776 | 0 | 8 | |i Print version: |t Neural networks in chemical reaction dynamics. |d New York : Oxford University Press, ©2012 |z 9780199765652 |w (DLC) 2010054098 |w (OCoLC)699373989 |
| 856 | 4 | 0 | |u https://ebookcentral.uam.elogim.com/lib/uam-ebooks/detail.action?docID=886617 |z Texto completo |
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