Practical Applications Of Machine Learning And Ai Medicine Environmental Science Transportation And Education
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Practical Applications of Machine Learning and AI: Medicine, Environmental Science, Transportation, and Education
Optimization, machine learning, and artificial intelligence are revolutionizing society, medicine, environmental science, transportation, and education. In medicine, AI-driven diagnostics and personalized treatments improve patient outcomes, while optimization streamlines resource allocation. Environmental science benefits from machine learning's ability to analyze complex datasets, enabling sustainable practices and climate predictions. In transportation, optimization enhances logistics and traffic flow, with AI powering autonomous vehicles and predictive maintenance. Across all areas, these technologies drive efficiency, innovation, and smarter decision-making. Practical Applications of Machine Learning and AI: Medicine, Environmental Science, Transportation, and Education provides deeper understanding of the complexities of optimization, machine learning and AI, examining their theoretical foundations. Furthermore, it contributes to the ongoing advancement of these fields, practical applications, and transformative potentials. Covering topics including Medical Image Segmentation, student performance prediction, and pothole detection, this book is an excellent resource for computer scientists, researchers, scholars, academicians, professionals, and more.
Intelligent and Fuzzy Systems
Artificial Intelligence in Human-Centric, Resilient & Sustainable Industries This book focuses on benefiting artificial intelligent tools in our business and social life under emerging conditions. Human-centric, resilient, and sustainable industries are built on ideals like human-centricity, ecological advantages, or social benefits. The mission of human-centric artificial intelligence is to improve people’s lives by offering solutions that boost productivity, accessibility to resources, security, well-being, and general quality of life. The latest intelligent methods and techniques on human-centric, resilient, and sustainable industries are introduced by theory and applications. This book covers the chapters of world-wide known experts on machine learning, medical image processing, process intelligence, process mining, and others. The intended readers are intelligent systems researchers, lecturers, M.Sc. and Ph.D. students trying to develop approaches giving human needs, values, and viewpoints top priority through artificial intelligent systems.
Optimization, Machine Learning, and Fuzzy Logic: Theory, Algorithms, and Applications
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.