Decision-making is a fundamental process that influences outcomes across a wide range of domains, including business, healthcare, scientific research, and automation. With the increasing availability of data and the growing computational power of modern systems, decision-making models have become more sophisticated and capable of providing highly accurate and efficient solutions. The ability to develop, analyze, and implement these models has become crucial for professionals and researchers working in fields that rely on data-driven decision-making. This book explores the evolution and…mehr
Decision-making is a fundamental process that influences outcomes across a wide range of domains, including business, healthcare, scientific research, and automation. With the increasing availability of data and the growing computational power of modern systems, decision-making models have become more sophisticated and capable of providing highly accurate and efficient solutions. The ability to develop, analyze, and implement these models has become crucial for professionals and researchers working in fields that rely on data-driven decision-making. This book explores the evolution and significance of decision systems, covering both foundational theories and advanced methodologies. It introduces readers to the essential principles of decision-making models, illustrating their applications through practical case studies and real-world scenarios. The discussion begins with a focus on traditional decision-making techniques and gradually progresses to more advanced topics, including machine learning-based approaches, the integration of artificial intelligence, and the role of fuzzy logic in decision support systems. Furthermore, ethical considerations in decision-making and strategies for mitigating bias are examined, ensuring that models remain fair and transparent. Throughout this book, each chapter builds on the previous one, providing a structured and comprehensive learning experience. By the time readers complete this book, they will have gained an in-depth understanding of decision-making frameworks, their applications, and the future directions of research in this dynamic field. Whether one is a student, a researcher, or an industry professional, this book serves as a valuable guide to mastering the complexities of decision systems and applying them effectively in various domains.
Dr. Pallavi Vijay Chavan is a Professor and Head in the Department of Information Technology, RAIT, D. Y. Patil Deemed to be University, NERUL, Navi Mumbai, India. During her 20-year career, she has worked on a variety of research topics, including Visual Cryptography, Image Processing, Intelligent Systems, Machine Learning, and Analytics. She has taught core subjects at the undergrad level, including DBMS, Theory of Computation, Artificial Neural Networks, and Soft Computing. Dr. Chavan is the author of dozens of research papers in international journals and conferences, including Springer, Elsevier, Inderscience and IEEE. Dr. Chavan is recipient of research grants from Mumbai University and is a member of ACM and ISTE. Dr. Chavan is the author of Automata Theory and Formal Languages from Elsevier Academic Press. Affiliations and expertise Professor & Head - Information Technology Ramrao Adik Institute of Technology, D Y Patil deemed to be University, India.
Inhaltsangabe
1. Introduction to Decision Systems 2. Foundations of Machine Learning 3. Fuzzy Logic and Fuzzy Set Theory 4. Artificial Neural Networks 5. Recurrent Networks 6. Associative Memories 7. Deep Learning 8. Integration of Machine Learning, Fuzzy Logic, and Artificial Neural Networks 9. Challenges and Opportunities in Decision Systems 10. Real World Applications of Decision Systems
1. Introduction to Decision Systems 2. Foundations of Machine Learning 3. Fuzzy Logic and Fuzzy Set Theory 4. Artificial Neural Networks 5. Recurrent Networks 6. Associative Memories 7. Deep Learning 8. Integration of Machine Learning, Fuzzy Logic, and Artificial Neural Networks 9. Challenges and Opportunities in Decision Systems 10. Real World Applications of Decision Systems
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