{"product_id":"9781483295657","title":"Neural Networks in Bioprocessing and Chemical Engineering","description":"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.\u003cbr\u003e\u003cbr\u003eEach chapter contains an introduction, chapter summary, references to further reading, practice problems, and a section on nomenclature\u003cbr\u003e Includes a PC-compatible disk containing input data files for examples, case studies, and practice problems\u003cbr\u003e Presents 10 detailed case studies\u003cbr\u003e Contains an extensive glossary, explaining terminology used in neural network applications in science and engineering\u003cbr\u003e Provides examples, problems, and ten detailed case studies of neural computing applications, including:\u003cbr\u003e Process fault-diagnosis of a chemical reactor\u003cbr\u003e Leonard–Kramer fault-classification problem\u003cbr\u003e Process fault-diagnosis for an unsteady-state continuous stirred-tank reactor system\u003cbr\u003e Classification of protein secondary-structure categories\u003cbr\u003e Quantitative prediction and regression analysis of complex chemical kinetics\u003cbr\u003e Software-based sensors for quantitative predictions of product compositions from flourescent spectra in bioprocessing\u003cbr\u003e Quality control and optimization of an autoclave curing process for manufacturing composite materials\u003cbr\u003e Predictive modeling of an experimental batch fermentation process\u003cbr\u003e Supervisory control of the Tennessee Eastman plantwide control problem\u003cbr\u003e Predictive modeling and optimal design of extractive bioseparation in aqueous two-phase systems","brand":"Elsevier Science","offers":[{"title":"Default Title","offer_id":47184734781680,"sku":"9781483295657","price":62.49,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0737\/7593\/9824\/files\/9781483295657_p0.jpg?v=1763626991","url":"https:\/\/shop-qa.barnesandnoble.com\/products\/9781483295657","provider":"Barnes \u0026 Noble (DEV)","version":"1.0","type":"link"}