Название: Optimization, Machine Learning, and Fuzzy Logic: Theory, Algorithms, and Applications
Автор: Toufik Mzili, Adarsh Kumar Arya, Dragan Pamucar, Momina Shaheen
Издательство: IGI Global
Год: 2025
Страниц: 620
Язык: английский
Формат: pdf (true), epub
Размер: 39.0 MB
Optimization, Machine Learning, and fuzzy logic are fundamental in the field of Computational Intelligence (CI), each contributing to solving complex problems across various domains. Optimization techniques focus on finding the best solutions to problems by improving efficiency and minimizing resources. Machine Learning enables systems to learn from data, making predictions or decisions without being programmed. Fuzzy logic deals with uncertainty and imprecision, allowing for flexible decision-making processes. Together, these theories, algorithms, and applications solve challenges in fields such as engineering, finance, and healthcare, where traditional methods often fall short. Optimization, Machine Learning, and Fuzzy Logic: Theory, Algorithms, and Applications explores optimization techniques, fuzzy logic, and their integration with Machine Learning. It covers fundamental concepts, mathematical foundations, algorithms, and applications, providing a holistic understanding of these domains. This book covers topics such as disease detection, Deep Learning, and text analysis, and is a useful resource for engineers, data scientists, medical professionals, academicians, and researchers.
