Decision Systems
Integrating Machine Learning, Fuzzy Logic, and Artificial Neural Networks
Published on 28. July 2025
Book
Paperback/Softback
270 pages
978-0-443-33728-4 (ISBN)
Description
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.
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.
More details
Language
English
Place of publication
San Francisco
United States
Publishing group
Elsevier Science & Technology
Target group
Professional and scholarly
Dimensions
Height: 235 mm
Width: 191 mm
Weight
450 gr
ISBN-13
978-0-443-33728-4 (9780443337284)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Other editions
Additional editions
Pallavi Vijay Chavan | Nisha Balani | Ramchandra Mangrulkar
Decision Systems
Integrating Machine Learning, Fuzzy Logic, and Artificial Neural Networks
E-Book
07/2025
Elsevier
€166.99
Available for download
Persons
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.
Dr. Nisha Balani serves is an Assistant Professor in the Department of Computer Science and Engineering at Jhulelal Institute of Technology in Nagpur, Maharashtra, India and Executive Director at First Impression Technologies, Nagpur. With a tenure spanning 17 years in academia, she has acquired expertise in the fields of data structures, algorithms, network security, artificial intelligence, machine learning, data science, and blockchain technology. Throughout her academic tenure, she has contributed significantly to her field, publishing research papers in esteemed journals indexed by SCI, Web of Science, Scopus, and UGC Care. Her academic qualifications include a Doctor of Philosophy (Ph.D.) in Computer Engineering from Ramrao Adik College of Engineering, Mumbai, a Master of Technology (M.Tech) in Computer Science and Engineering obtained in 2012, and a Bachelor of Engineering (B.E) in Information Technology in 2008 from Shri Ramdeobaba College of Engineering, Nagpur. Guided by the belief that knowledge transforms possibilities, she is dedicated to igniting the spark of discovery and fostering a culture of continuous learning.
Affiliations and expertise
1. Assistant Professor, Department of Computer Science and Engineering, Jhulelal Institute of Technology, Nagpur, India.
2. Executive Director, First Impression Technologies, Nagpur, India.
Dr. Mangrulkar is a Professor of Information Technology at Dwarkadas Sanghvi College of Engineering and has 20 years of teaching experience in the field of intelligent systems and security. He completed his M.Sc. in Computer Science and Engineering from NIT Rourkela. He completed his Ph.D. in Information Security from SGBAU, Amravati. Dr. Mangrulkar is the recipient of grants from UGC as well as AICTE.
Affiliations and expertise
Professor, Department of Information Technology, Dwarkadas Sanghvi College of Engineering, India.
Dr. Sangita Santosh Chaudhari obtained her Master of Computer Engineering from Mumbai University in 2008 and Ph. D. in GIS and Remote Sensing from Indian Institute of Technology Bombay in 2016. Currently, she is working as a Professor and Head of Department of Information Technology at Ramrao Adik Institute of Technology, D. Y. Patil Deemed to be University, Nerul, Navi Mumbai.
Dr. Chaudhari has over 100 research papers to her credit published in peer reviewed and referred National and International Journals and Conferences. She is the co-editor of Advances in Scalable and Intelligent Geospatial Analytics: Challenges and Applications from Taylor & Francis/CRC Press, Intelligent Solutions for Cognitive Disorders from IGI Global, and Computational Intelligence in Image and Video Processing from Taylor & Francis/Chapman & Hall/CRC Press. She is an IEEE senior member and active member of IEEE GRSS and IEEE Women in Engineering. Her research interests include Image processing, Information security, Data Analytics, Geographical Information Systems, and Remote sensing.
Affiliations and expertise
Professor and Head, Department of Computer Science and Engineering, Ramrao Adik Institute of Technology, D. Y. Patil Deemed to be University, India.
Affiliations and expertise
Professor & Head - Information Technology Ramrao Adik Institute of Technology, D Y Patil deemed to be University, India.
Dr. Nisha Balani serves is an Assistant Professor in the Department of Computer Science and Engineering at Jhulelal Institute of Technology in Nagpur, Maharashtra, India and Executive Director at First Impression Technologies, Nagpur. With a tenure spanning 17 years in academia, she has acquired expertise in the fields of data structures, algorithms, network security, artificial intelligence, machine learning, data science, and blockchain technology. Throughout her academic tenure, she has contributed significantly to her field, publishing research papers in esteemed journals indexed by SCI, Web of Science, Scopus, and UGC Care. Her academic qualifications include a Doctor of Philosophy (Ph.D.) in Computer Engineering from Ramrao Adik College of Engineering, Mumbai, a Master of Technology (M.Tech) in Computer Science and Engineering obtained in 2012, and a Bachelor of Engineering (B.E) in Information Technology in 2008 from Shri Ramdeobaba College of Engineering, Nagpur. Guided by the belief that knowledge transforms possibilities, she is dedicated to igniting the spark of discovery and fostering a culture of continuous learning.
Affiliations and expertise
1. Assistant Professor, Department of Computer Science and Engineering, Jhulelal Institute of Technology, Nagpur, India.
2. Executive Director, First Impression Technologies, Nagpur, India.
Dr. Mangrulkar is a Professor of Information Technology at Dwarkadas Sanghvi College of Engineering and has 20 years of teaching experience in the field of intelligent systems and security. He completed his M.Sc. in Computer Science and Engineering from NIT Rourkela. He completed his Ph.D. in Information Security from SGBAU, Amravati. Dr. Mangrulkar is the recipient of grants from UGC as well as AICTE.
Affiliations and expertise
Professor, Department of Information Technology, Dwarkadas Sanghvi College of Engineering, India.
Dr. Sangita Santosh Chaudhari obtained her Master of Computer Engineering from Mumbai University in 2008 and Ph. D. in GIS and Remote Sensing from Indian Institute of Technology Bombay in 2016. Currently, she is working as a Professor and Head of Department of Information Technology at Ramrao Adik Institute of Technology, D. Y. Patil Deemed to be University, Nerul, Navi Mumbai.
Dr. Chaudhari has over 100 research papers to her credit published in peer reviewed and referred National and International Journals and Conferences. She is the co-editor of Advances in Scalable and Intelligent Geospatial Analytics: Challenges and Applications from Taylor & Francis/CRC Press, Intelligent Solutions for Cognitive Disorders from IGI Global, and Computational Intelligence in Image and Video Processing from Taylor & Francis/Chapman & Hall/CRC Press. She is an IEEE senior member and active member of IEEE GRSS and IEEE Women in Engineering. Her research interests include Image processing, Information security, Data Analytics, Geographical Information Systems, and Remote sensing.
Affiliations and expertise
Professor and Head, Department of Computer Science and Engineering, Ramrao Adik Institute of Technology, D. Y. Patil Deemed to be University, India.
Author
Associate Professor - Information Technology Ramrao Adik Institute of Technology, D Y Patil deemed to be University, India
Head of the Department of Computer Science and Engineering, specializing in Artificial Intelligence and Machine Learning, Jhulelal Institute of Technology, India
Assistant Professor - Computer Engineering Dwarkadas Sanghvi College of Engineering, India
Professor and Head of Department of Information Technology at Ramrao Adik Institute of Technology, D. Y. Patil Deemed to be University, India
Content
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
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