Advances on Mathematical Modeling and Optimization with Its Applications (eBook, ePUB)

Redaktion: Mukherjee, Gunjan; Chaudhary, Aryan; Kar, Rahul; Basu Mallik, Biswadip

• Format: ePub

Produktbeschreibung

Discusses machine learning models and their optimization in mathematical modeling. Covers important topics such as linear integer programming, network design problems, mixed integer problems, constrained and unconstrained optimization, constrained integer programming, and gradient-based nonlinear optimization.

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Produktdetails

• Verlag: Taylor & Francis
• Seitenzahl: 310
• Erscheinungstermin: 28. März 2024
• Englisch
• ISBN-13: 9781040001363
• Artikelnr.: 69933745

Autorenporträt

Dr. Gunjan Mukherjee is currently an associate professor in the Department of Computational Sciences at Brainware University. He completed his BSc in Physics from Calcutta University, MCA from IGNOU, MTech from Calcutta University and earned his PhD in Engineering from Jadavpur University. His areas of research interests include computer vision, machine learning, soft computing, image processing, etc. He is a life member of CSI, ISOC, and IAENG and has published a number of papers in journals and international conferences of repute. Dr. Mukherjee guided many students of BTech and MCA in their projects and research works. He has solely authored the school computer book series (classes 3-10), a textbook on IT systems theory for engineering students, and is presently writing a book on Python technology. He is currently attached to a reputed publishing house for publication of question/answer¿based books for diploma and engineering level students. He has acted as a reviewer for many technical books. Dr. Gunjan was an assistant teacher at the Sree Aurobindo Institute of Education, an education officer in CSI, Kolkata chapter, a senior faculty in NIT Ltd, and a lecturer at Calcutta Institute of Technology. He also served as a visiting faculty in Aliha University, Techno India College and JIS College. Dr. Biswadip Basu Mallik is presently an Associate Professor of Mathematics in the Department of Basic Sciences and Humanities at Institute of Engineering & Management, Kolkata, India. He has been involved in teaching and research for almost 22 years and has published several research papers and book chapters in various scientific journals and with reputed publishers. He has authored five books at undergraduate levels in the areas of Engineering Mathematics, Quantitative Methods and Computational Intelligence. He has also published five Indian patents along with thirteen edited books. His fields of research work are Computational Fluid Dynamics, Mathematical Modelling, Machine Learning, and Optimization. Dr. Basu Mallik is a Managing editor of Journal of Mathematical Sciences & Computational Mathematics (JMSCM), USA. He is also an Editorial board member and reviewer of several scientific journals. He is a senior life member of Operational Research Society of India (ORSI) and a life member of Calcutta Mathematical Society (CMS), Indian Statistical Institute (ISI), Indian Science Congress Association (ISCA), and International Association of Engineers (IAENG). Rahul Kar has an M.Sc. in Pure Mathematics and is pursuing his PhD from Bankura University. He currently works as a Faculty of Mathematics at Kalyani Mahavidyalaya, Kalyani, Nadia, West Bengal. He has served as a guest faculty of the Gurunanak Institute of Technology and two other colleges. In total, he has 7 years of teaching experience. Rahul has published many research papers with the Scopus index and is an editor of four national and international journals and a reviewer of five international journals. He has been an editor for ten mathematics/computer books and is an annual member of the Indian Mathematical Society as well as an honorary member of Carmels Research Institute, Dakar, Senegal. Aryan Chaudhary is the Chief Scientific Advisor at BioTech Sphere Research, India, having served as the Research Head at Nijji HealthCare Pvt Ltd, Head of Research, Nuvem Resources, and other invited positions. He has demonstrated his expertise in leveraging revolutionary technologies such as artificial intelligence, deep learning, IoT, cognitive technology, and blockchain to revolutionize the healthcare landscape. His relentless pursuit of excellence and innovation has earned him recognition as a thought leader in the industry. His dedication to advancing healthcare is evident through his vast bodies of work. He has authored several influential academic papers on public health and digital health, published in prestigious international journals. His research primarily focuses on integrating IoT and sensor technology for efficient data collection through one¿time and ambulatory monitoring. As a testament to his expertise and leadership, he is not only a keynote speaker at numerous international and national conferences but also serves as the Series Editor of a CRC book series and is the editor of several books on biomedical science. His commitment to the advancement of scientific knowledge extends further, as he acts as a guest editor for special issues in renowned journals. Recognized for his significant contributions, he has received prestigious accolades, including the "Most Inspiring Young Leader in Healthtech Space 2022" by Business Connect, and the title of the best project leader at Global Education and Corporate Leadership. Moreover, he holds senior memberships in various international science associations, reflecting his influence and impact in the field. Adding to his accomplishments, Aryan Chaudhary is currently serving as a Guest Editor for a special issue in the highly regarded Journal: EAI Endorsed Transactions on AI and Robotics, and he has joined the Editorial Board of Biomedical Science and Clinical Research (BSCR). Additionally, he is a respected professional member of the Association for Computing Machinery (ACM). Recently, he has been elected as Chair for the ACM Professional Chapter.

Inhaltsangabe

1. Mathematical Modeling and Technology. 2. Modeling with Discrete
Dynamical Systems. 3. Differential Equations in the Modeling Perception. 4.
Regression Methods and Models. 5. Linear Integer Programming. 6. Mixed
Integer Programming. 7. Single Variable and Multivariable Optimization. 8.
Nonlinear Optimization Methods. 9. Simulation Models. 10. Model based on
the Decision Making. 11. Multi-Attribute Decision Modeling. 12.
Mathematical Models in Machine Learning. 13. Application of Mathematical
Models in the Deep Learning Model. 14. Optimization in the Machine Learning
Models.