Neural Networks in Bioprocessing and Chemical Engineering

By D. Richard Baughman and Y.A. Liu

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.

• Format: Hardcover
• Language: English
• ISBN: 0120830302
• ISBN13: 9780120830305
• Release Date: March 1996
• Publisher: Academic Press
• Length: 488 Pages
• Weight: 1.45 lbs.
• Dimensions: 1.2" x 5.9" x 9.0"

Customer Reviews

See an objective published review below.

IIE Transactions, the leading journal in industrial and systems engineering, gives the following review comments in its Volume 29, No. 9, pages 810-811, September (1997) "This book introduces the basic concepts and practice of neural networks, emphasizing their applications in the bioprocessing and chemical engineering fields. The authors have developed an excellent, well researched text that links the theory and practice of neural network modeling. The book is timely and presents a well-organized treatment of this emerging research area.......... In summary, this is an excellent introductory text on neural networks for use in bioprocessing and chemical engineering applications. The book could be used in either a senior undergraduate or graduate engineering course. The authors have blended theory and practice to create a very useful text that offers ideas for future research, yet also can be used in a pragmatic way to design neural networks. This is one of the best books that I have read on the topic of neural computing in engineering."

Data Files

Please show me a detailed data file in voidtst.nna .Thanks