optimization machine learning fuzzy (9 risultati)

Condizione: New. In.

Buch. Condizione: Neu. Neuware - The book investigates the correlation between computational optimization methods, data science, machine learning, and mathematical analysis. This book provides profound insights into the mathematical analysis of machine learning models. In this book, case studies are presented in a variety of disciplines, such as healthcare , finance , and e-commerce. The latter illustrates the practical implementations of optimisation in the selection of features, hyperparameters, and models. Practical observations regarding the evaluation and enhancement of machine learning models in real-world scenarios, including agriculture, e-commerce, healthcare, and financial portfolio management, are included in this publication. This publication is intended for researchers, engineers, mathematicians, and computer scientists. The goal is to improve the utilisation of computational optimisation techniques in real-time scenarios by integrating theoretical concepts with practical applications.

Condizione: New. In.

hardcover. Condizione: Very Good.

Taschenbuch. Condizione: Neu. A Renewable Energy Selection Model for Sustainable Development | Integrating Hesitant Fuzzy Logic and Machine Learning for Renewable Energy Optimization | Virendra Singh Rana (u. a.) | Taschenbuch | Englisch | 2025 | LAP LAMBERT Academic Publishing | EAN 9786208437046 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu Print on Demand.

Taschenbuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering.

Paperback. Condizione: new. 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. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.

Taschenbuch. Condizione: Neu. Optimization, Machine Learning, and Fuzzy Logic | Theory, Algorithms, and Applications | Toufik Mzili (u. a.) | Taschenbuch | Englisch | 2025 | IGI Global | EAN 9798369373538 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu Print on Demand.

Hardcover. Condizione: new. Hardcover. 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. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.