Neural Networks in Bioprocessing and Chemical Engineering

Nonfiction, Computers, Advanced Computing, Engineering, Neural Networks, Science & Nature, Science, Biological Sciences, Biotechnology, General Computing
Cover of the book Neural Networks in Bioprocessing and Chemical Engineering by D. R. Baughman, Y. A. Liu, Elsevier Science
View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart
Author: D. R. Baughman, Y. A. Liu ISBN: 9781483295657
Publisher: Elsevier Science Publication: June 28, 2014
Imprint: Academic Press Language: English
Author: D. R. Baughman, Y. A. Liu
ISBN: 9781483295657
Publisher: Elsevier Science
Publication: June 28, 2014
Imprint: Academic Press
Language: English

Neural networks have received a great deal of attention among scientists and engineers. In chemical engineering, neural computing has moved from pioneering projects toward mainstream industrial applications. This book introduces the fundamental principles of neural computing, and is the first to focus on its practical applications in bioprocessing and chemical engineering. Examples, problems, and 10 detailed case studies demonstrate how to develop, train, and apply neural networks. A disk containing input data files for all illustrative examples, case studies, and practice problems provides the opportunity for hands-on experience. An important goal of the book is to help the student or practitioner learn and implement neural networks quickly and inexpensively using commercially available, PC-based software tools. Detailed network specifications and training procedures are included for all neural network examples discussed in the book.

Each chapter contains an introduction, chapter summary, references to further reading, practice problems, and a section on nomenclature
Includes a PC-compatible disk containing input data files for examples, case studies, and practice problems
Presents 10 detailed case studies
Contains an extensive glossary, explaining terminology used in neural network applications in science and engineering
Provides examples, problems, and ten detailed case studies of neural computing applications, including:
Process fault-diagnosis of a chemical reactor
Leonard–Kramer fault-classification problem
Process fault-diagnosis for an unsteady-state continuous stirred-tank reactor system
Classification of protein secondary-structure categories
Quantitative prediction and regression analysis of complex chemical kinetics
Software-based sensors for quantitative predictions of product compositions from flourescent spectra in bioprocessing
Quality control and optimization of an autoclave curing process for manufacturing composite materials
Predictive modeling of an experimental batch fermentation process
Supervisory control of the Tennessee Eastman plantwide control problem
Predictive modeling and optimal design of extractive bioseparation in aqueous two-phase systems

View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart

Neural networks have received a great deal of attention among scientists and engineers. In chemical engineering, neural computing has moved from pioneering projects toward mainstream industrial applications. This book introduces the fundamental principles of neural computing, and is the first to focus on its practical applications in bioprocessing and chemical engineering. Examples, problems, and 10 detailed case studies demonstrate how to develop, train, and apply neural networks. A disk containing input data files for all illustrative examples, case studies, and practice problems provides the opportunity for hands-on experience. An important goal of the book is to help the student or practitioner learn and implement neural networks quickly and inexpensively using commercially available, PC-based software tools. Detailed network specifications and training procedures are included for all neural network examples discussed in the book.

Each chapter contains an introduction, chapter summary, references to further reading, practice problems, and a section on nomenclature
Includes a PC-compatible disk containing input data files for examples, case studies, and practice problems
Presents 10 detailed case studies
Contains an extensive glossary, explaining terminology used in neural network applications in science and engineering
Provides examples, problems, and ten detailed case studies of neural computing applications, including:
Process fault-diagnosis of a chemical reactor
Leonard–Kramer fault-classification problem
Process fault-diagnosis for an unsteady-state continuous stirred-tank reactor system
Classification of protein secondary-structure categories
Quantitative prediction and regression analysis of complex chemical kinetics
Software-based sensors for quantitative predictions of product compositions from flourescent spectra in bioprocessing
Quality control and optimization of an autoclave curing process for manufacturing composite materials
Predictive modeling of an experimental batch fermentation process
Supervisory control of the Tennessee Eastman plantwide control problem
Predictive modeling and optimal design of extractive bioseparation in aqueous two-phase systems

More books from Elsevier Science

Cover of the book Nanoneuroprotection and Nanoneurotoxicology by D. R. Baughman, Y. A. Liu
Cover of the book Polarized Light in Optics and Spectroscopy by D. R. Baughman, Y. A. Liu
Cover of the book The Alkaloids by D. R. Baughman, Y. A. Liu
Cover of the book Learning About Learning Disabilities by D. R. Baughman, Y. A. Liu
Cover of the book Fischer-Tropsch Synthesis, Catalysts and Catalysis by D. R. Baughman, Y. A. Liu
Cover of the book The Future of the Financial Exchanges by D. R. Baughman, Y. A. Liu
Cover of the book Advances in Photovoltaics: Part 1 by D. R. Baughman, Y. A. Liu
Cover of the book Neoproterozoic-Cambrian Tectonics, Global Change and Evolution by D. R. Baughman, Y. A. Liu
Cover of the book Neurobiology of Disease by D. R. Baughman, Y. A. Liu
Cover of the book Glucose Intake and Utilization in Pre-Diabetes and Diabetes by D. R. Baughman, Y. A. Liu
Cover of the book Exceptional Life Journeys by D. R. Baughman, Y. A. Liu
Cover of the book COMPUTER SOLUTION OF LARGE LINEAR SYSTEMSSTUDIES IN MATHEMATICS AND ITS APPLICATIONS VOLUME 28 (SMIA) by D. R. Baughman, Y. A. Liu
Cover of the book Evidence-Based Climate Science by D. R. Baughman, Y. A. Liu
Cover of the book The Art and Science of Digital Compositing by D. R. Baughman, Y. A. Liu
Cover of the book Nanostructures for Antimicrobial Therapy by D. R. Baughman, Y. A. Liu
We use our own "cookies" and third party cookies to improve services and to see statistical information. By using this website, you agree to our Privacy Policy