Description
Product ID: | 9781032273372 |
Product Form: | Hardback |
Country of Manufacture: | GB |
Title: | Optimization of Sustainable Enzymes Production |
Subtitle: | Artificial Intelligence and Machine Learning Techniques |
Authors: | Author: J Satya Eswari, Nisha Suryawanshi |
Page Count: | 220 |
Subjects: | Biotechnology, Biotechnology, Automatic control engineering, Environmental science, engineering and technology, Information technology: general topics, Supercomputers, Algorithms and data structures, Computer science, Computer architecture and logic design, Artificial intelligence, Machine learning, Automatic control engineering, Environmental science, engineering & technology, Information technology: general issues, Supercomputers, Algorithms & data structures, Computer science, Computer architecture & logic design, Artificial intelligence, Machine learning |
Description: | Select Guide Rating This book presents a systematic approach to analyze evolutionary and nature-inspired population-based search algorithms. The book presents current research on various applications of machine learning and discusses optimization techniques to solve real-life problems. 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 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. |
Imprint Name: | Chapman & Hall/CRC |
Publisher Name: | Taylor & Francis Ltd |
Country of Publication: | GB |
Publishing Date: | 2022-11-29 |