This book is designed as a reference book and presents a systematic approach to analyze evolutionary and nature-inspired population-based search algorithms. Beginning with an introduction to optimization methods and algorithms and various enzymes, the book then moves on to provide a unified framework of process optimization for enzymes with various algorithms. The book presents current research on various applications of machine learning and discusses optimization techniques to solve real-life problems.

The book compiles the different machine learning models for optimization of process parameters for production of industrially important enzymes. The production and optimization of various enzymes produced by different microorganisms are elaborated in the book
It discusses the optimization methods that help minimize the error in developing patterns and classifications, which further helps improve prediction and decision-making
Covers the best-performing methods and approaches for optimization sustainable enzymes production with AI integration in a real-time environment
Featuring valuable insights, the book helps readers explore new avenues leading towards multidisciplinary research discussions

The book is aimed primarily at advanced undergraduates and graduates studying machine learning, data science and industrial biotechnology. Researchers and professionals will also find this book useful.

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Yes, you can access Optimization of Sustainable Enzymes Production by J Satya Eswari, Nisha Suryawanshi, J Satya Eswari, Nisha Suryawanshi in PDF and/or ePUB format, as well as other popular books in Computer Science & Computer Science General. We have over one million books available in our catalogue for you to explore.

Information

Publisher

Chapman and Hall/CRC

Year

2022

ISBN

9781000787757

Edition

Topic

Computer Science

Subtopic

Computer Science General

Index

Computer Science

Cover Page
Half Title page
Title Page
Copyright Page
Contents
Preface
Editors
Contributors
1 Industrially Important Enzymes
2 Applications of Industrially Important Enzymes
3 Optimization of Fermentation Process: Influence on Industrial Production of Enzymes
4 Reforming Process Optimization of Enzyme Production Using Artificial Intelligence and Machine Learning
5 Scale-Up Models for Chitinase Production, Enzyme Kinetics, and Optimization
6 Genetic Algorithm for Optimization of Fermentation Processes of Various Enzyme Productions
7 Optimization of Process Parameters of Various Classes of Enzymes Using Artificial Neural Network
8 Advanced Evolutionary Differential Evolution and Central Composite Design: Comparative Study for Process Optimization of Chitinase Production
9 Artificial Bee Colony for Optimization of Process Parameters for Various Enzyme Productions
Index