Mathematical Modeling for Intelligent Systems
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This book provides a reference for the applications of mathematical modeling using intelligent techniques in various unique industry problems in the era of Industry 4.0. Providing a thorough introduction to the field of soft computing techniques, the book covers every major technique in AI in a clear and practical style.

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Produktbeschreibung
This book provides a reference for the applications of mathematical modeling using intelligent techniques in various unique industry problems in the era of Industry 4.0. Providing a thorough introduction to the field of soft computing techniques, the book covers every major technique in AI in a clear and practical style.
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Autorenporträt
Dr. Mukesh Kumar Awasthi working as an Assistant Professor in the Department of Mathematics at Babasaheb Bhimrao Ambedkar University (A Central University), Lucknow, India. He completed his doctorate with a major in Mathematics from the Indian Institute of Technology Roorkee, Roorkee, India in 2012. He has qualified for various National level competitive exams in the area of Mathematical Sciences. He has been a recipient of a research fellowship under the Council of Scientific and Industrial Research, India during his Ph.D. His research areas include Computational Fluid Dynamics, Heat transfer, Applied Mathematical Modeling, and Numerical analysis, etc. He loves to teach applied mathematics courses to undergraduate, postgraduate, and Ph.D. students. He has been indifferent to academic and administrative positions during his academic profession. He has more than 100 publications (90 SCI indexed, 92 Scopus indexed) to his credit in the high impact factor journals of international repute. He has attended many symposia, workshops, and conferences in mathematics as well as fluid mechanics. He has got research awards consecutively four times from the University of Petroleum and Energy Studies, Dehradun, India. He has also received the start-up research fund for his project "Nonlinear study of the interface in multilayer fluid system" from UGC, New Delhi. Dr Ravi Tomar is currently working as Associate Professor in the School of Computer Science at the University of Petroleum & Energy Studies, Dehradun, India. Skilled in Programming, Computer Networking, Stream processing, Core Java, J2EE, RPA and CorDApp, his research interests include Wireless Sensor Networks, Image Processing, Data Mining and Warehousing, Computer Networks, big data technologies and VANET. He has authored 51+ papers in different research areas, filled four Indian patent, edited 5 books and have authored 5 books. He has delivered Training to corporates nationally and internationally on Confluent Apache Kafka, Stream Processing, RPA, CordaApp, J2EE and IoT to clients like KeyBank, Accenture, Union Bank of Philippines, Ernst and Young and Deloitte. Dr Tomar is officially recognized as Instructor for Confluent and CordApp. He has conducted various International conferences in India, France and Nepal. He has been awarded a young researcher in Computer Science and Engineering by RedInno, India in 2018, Academic Excellence and Research Excellence Award by UPES in 2021 and Young Scientist Award by UCOST, Dehradun . Dr. Maanak Gupta is an Assistant Professor in the Department of Computer Science at Tennessee Tech University, USA. He received his Ph.D. in Computer Science from the University of Texas at San Antonio and has worked as a Postdoctoral Research Fellow at the Institute for Cyber Security. He also holds an M.S. degree in Information Systems from Northeastern University, Boston. His primary area of research includes security and privacy in cyberspace focused on studying foundational aspects of access control and their application in technologies including cyber-physical systems, cloud computing, IoT, and Big data. Dr. Gupta has worked in developing novel security mechanisms, models, and architectures for next-generation smart cars, smart cities, intelligent transportation systems, and smart farming. He is also interested in machine learning-based malware analysis and AI-assisted cyber security solutions. His scholarly work is regularly published at top peer-reviewed security venues including ACM SIGSAC conferences and refereed journals. He was awarded the 2019 computer science outstanding doctoral dissertation research award from UT San Antonio. His research has been funded by the US National Science Foundation (NSF), NASA, the US Department of Defense (DoD), and private industry.