Methods in Industrial Biotechnology for Chemical Engineers
W.B. Vasantha Kandasamy, Florentin Smarandache

TL;DR
This paper explores the application of fuzzy, neutrosophic, and genetic algorithms to solve various chemical industry problems, emphasizing pollution control, process optimization, and waste minimization.
Contribution
It introduces the use of fuzzy and neutrosophic models in chemical engineering problems, providing novel solutions for pollution, flow rates, and process optimization.
Findings
Fuzzy control effectively reduces pollution in cement industries.
Neutrosophic models handle indeterminacy in chemical processes.
Genetic algorithms optimize raw material proportions.
Abstract
In keeping with the definition that biotechnology is really no more than a name given to a set of techniques and processes, the authors apply some set of fuzzy techniques to chemical industry problems such as finding the proper proportion of raw mix to control pollution, to study flow rates, to find out the better quality of products. We use fuzzy control theory, fuzzy neural networks, fuzzy relational equations, genetic algorithms to these problems for solutions. When the solution to the problem can have certain concepts or attributes as indeterminate, the only model that can tackle such a situation is the neutrosophic model. The authors have also used these models in this book to study the use of biotechnology in chemical industries. This book has six chapters. First chapter gives a brief description of biotechnology. Second chapter deals will proper proportion of mix of raw…
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Taxonomy
TopicsAdvanced Control Systems Optimization · Process Optimization and Integration · Cognitive Science and Mapping
