Optimization, Machine Learning, and Fuzzy Logic: Theory, Algorithms, and Applications (Paperback)

Toufik Mzili

/ ISBN 13: 9798369373538

Editore: IGI Global, Hershey, PA, 2025

Paperback. Optimization, machine learning, and fuzzy logic are fundamental in the field of computational intelligence, 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. The continued application and exploration of these disciplines may unveil new possibilities for advanced problem-solving and intelligent systems. 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. "This publication offers a comprehensive exploration of 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"-- Provided by publisher. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability. Codice articolo 9798369373538

Riassunto:

Optimization, machine learning, and fuzzy logic are fundamental in the field of computational intelligence, 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. The continued application and exploration of these disciplines may unveil new possibilities for advanced problem-solving and intelligent systems. 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.

Dati bibliografici

Titolo: Optimization, Machine Learning, and Fuzzy ...
Casa editrice: IGI Global, Hershey, PA
Data di pubblicazione: 2025
Legatura: Paperback
Condizione: new