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Applications of Mathematical Modeling, Machine Learning, and Intelligent Computing for Industrial Development -

Applications of Mathematical Modeling, Machine Learning, and Intelligent Computing for Industrial Development

Buch | Softcover
404 Seiten
2024
CRC Press (Verlag)
978-1-032-47929-3 (ISBN)
CHF 99,45 inkl. MwSt
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The text presents emerging real-life topics on mathematical models, machine learning, and intelligent computing in a single volume. It will serve as an ideal text for senior undergraduate, graduate students, and researchers in diverse fields domains including industrial and manufacturing engineering, computer engineering, and mathematics.
The text focuses on mathematical modeling and applications of advanced techniques of machine learning, and artificial intelligence, including artificial neural networks, evolutionary computing, data mining, and fuzzy systems to solve performance and design issues more precisely. Intelligent computing encompasses technologies, algorithms, and models in providing effective and efficient solutions to a wide range of problems, including the airport’s intelligent safety system. It will serve as an ideal reference text for senior undergraduate, graduate students, and academic researchers in fields that include industrial engineering, manufacturing engineering, computer engineering, and mathematics.

The book:



Discusses mathematical modeling for traffic, sustainable supply chain, vehicular Ad-Hoc networks, and internet of things networks with intelligent gateways
Covers advanced machine learning, artificial intelligence, fuzzy systems, evolutionary computing, and data mining techniques for real- world problems
Presents applications of mathematical models in chronic diseases such as kidney and coronary artery diseases
Highlights advances in mathematical modeling, strength, and benefits of machine learning and artificial intelligence, including driving goals, applicability, algorithms, and processes involved
Showcases emerging real-life topics on mathematical models, machine learning, and intelligent computing using an interdisciplinary approach

The text presents emerging real-life topics on mathematical models, machine learning, and intelligent computing in a single volume. It will serve as an ideal text for senior undergraduate students, graduate students, and researchers in diverse fields, including industrial and manufacturing engineering, computer engineering, and mathematics.

MADHU JAIN is presently working as an Associate Professor in the Department of Mathematics, Indian Institute of Technology Roorkee, India. Before joining IIT Roorkee, she served as Reader/Associate Professor/Professor in the Department of Mathematics in Dr. B.R.A. University, Agra, for 10 years (1999 - 2008) and as visiting faculty in Indian Institute of Technology, Delhi (1994-1997). She has published over 400 research papers in International Journals, over 100 papers in Conference Proceeding/edited books, and 20 books. She was conferred Young Scientist Award & SERC Visiting Fellow of the Department of Science and Technology (DST), India, and Career Award of University Grant Commission (UGC), India. For outstanding contribution in research, IT Vikas Parisad, India conferred her Vigyan Gaurav award (2007). She is the recipient of the Distinguish Service Award (2011) of Vijnana Parisad of India for her outstanding contributions to Mathematics. She was Visiting Fellow of Isaac Newton Institute of Mathematical Sciences, Cambridge, UK, for during summer in 2010, 2011 & 2014. At present, Dr. Madhu Jain is holding the post of President of Vijnana Parisad of India, Secretary of Operations Research Society of India, Agra Chapter, and General Secretary of Global Society of Mathematical and Allied Sciences. She has participated over 150 International/National Conferences in India and Abroad and visited many reputed universities/Institutes in USA, Canada, Australia, UK, Germany, France, Holland, Belgium, Taiwan, UAE. Her current research interest includes Performance modeling of Computer Communication Networks (CCN), Queueing theory, Software and hardware reliability, Supply chain management, Bio-informatics, Soft computing, etc. DINESH K. SHARMA is a Professor of Quantitative Methods and Computer Applications in the Department of Business, Management and Accounting at the University of Maryland Eastern Shore, USA. He earned his MS in Mathematics, MS in Computer Science, a Ph.D. in Operations Research, and a second Ph.D. in Management. Professor Sharma has over twenty-eight years of teaching experience, has served on several committees to supervise Ph.D. students, and acts as an external Ph.D. thesis examiner for several universities in India. Dr. Sharma's research interests include mathematical programming, artificial intelligence and machine learning techniques, supply chain management, healthcare management, and portfolio management. He has published over 250 refereed journal articles and conference proceedings and has also won fifteen best paper awards. Professor Sharma has collaborated on a number of funded research grants. Professor Sharma is the Editor of the Journal of Global Information Technology and Review of Business and Technology Research and is on the editorial board of several journals and a paper reviewer for many additional journals and conferences. Additionally, he is a member of Decision Sciences (USA), a life member of the Operational Research Society of India, and served as a program chair and coordinator of several international conferences in many countries. RAKHEE KULSHRESTHA is faculty in the Department of Mathematics, Birla Institute of Technology and Science, Pilani. She has received Bachelor of Science, Master of Science in Operations Research from Dr. B.R. Ambedker University, Agra. She has completed her Ph.D. from Centre for Information and Decision Sciences, B.R. Ambedkar University, Agra. There are more than 30 research publications in refereed International/National journals/proceedings, a monograph and a patent to her credit. She has participated in over 40 International/National Conferences in India and Abroad and visited many reputed universities/Institutes in Germany, Turkey, Singapore. Her research interests include the areas of applied probability, performance analysis of communication networks, inventory and supply chain management. H.S. HOTA is a Professor and Department Head at Atal Bihari Vajpayee University in Bilaspur. He earned his Ph.D. from Guru Ghasidas Central University in Bilaspur. His research interests include Artificial Intelligence and Machine Learning, Business Intelligence, Information Security, and Data Mining, and he has published over 75 refereed journal articles in reputable journals. In conference proceedings, more than 60 articles have been published. He has also won five best paper awards at international conferences. He has also been to several countries and spoken at international conferences.

Section 1: Mathematical Modeling

Chapter 1
An Interactive Weight-Based Portfolio System Using Goal Programming
Hari Sharma, Kate Brown, Vineet Kumar Awasthi

Chapter 2
Generalized knowledge measure based on hesitant fuzzy sets with application to MCDM
Dinesh K. Sharma, Surender Singh, Sumita Lalotra

Chapter 3
Queuing System with Customers’ Impatience, Retention and Feedback
Rakesh Kumar, Bhupender Kumar Som, K. Kalidass, M. I. G. Suranga Sampath

Chapter 4
Controllable Multiprocessor Queueing System
Anamika Jain, Madhu Jain, Dheeraj Bhardwaj

Chapter 5
Multi-server Queuing system with Feedback and Retention
Rakesh Kumar, Sapana Sharma, Bhavneet Singh Soodan

Chapter 6
Retrial Queueing System Subject to Differentiated Vacations with Impatience Customers
M. I. G. Suranga Sampath, Dinesh K. Sharma, Avinash Gaur

Chapter 7
A Preorder discounts and online payment facility on a sustainable inventory model with controllable carbon emission
S.R Singh, Dipti Singh

Chapter 8
Green Inventory Systems with Two-Warehouses for Rubber Waste Items
Ajay Singh Yadav, Palak Mehta, Natesan Thillagovindan

Section 2: Machine Learning
Chapter 9
Cyber Attack Detection Applying Machine Learning Approaches
Vikash Kumar, Ditipriya Sinha, Ayan Kumar Das

Chapter 10
Feature Extraction Methods for Intelligent Audio Signal Classification
Aaron Rababaah

Chapter 11
Feature Detection & Extraction Techniques with Different Similarity Measures Using Bag of Features Model
Roohi Ali, Manish Maheshwari

Chapter 12
Stratification Based Initialization Model on Partitional Clustering for Big Data Mining
Kamlesh Kumar Pandey, Diwakar Shukla

Chapter 13
Regression Ensemble Techniques for Prediction of Financial Time Series Data
Richa Handa, H.S. Hota, Julius A. Alade

Chapter 14
Intelligent System for Integrating Customer’s Voice with CAD for Seat Comfort
Saed Talib Amer, Landon Onyebueke, Aaron Rababaah

Chapter 15
An Implementation of Machine Learning to Detect Real Time Web Application Vulnerability
Tarun Dhar Diwan, Siddartha Choubey, H.S. Hota

Section 3: Intelligent Computing

Chapter 16
Intelligent Decision Support System for Air Traffic Management
Aaron Rababaah, Mohamed Siddig

Chapter 17
Bio-Mechanical Hand With Wide Degree Of Freedom
Ankit, Rohtash Dhiman

Chapter 18
Analyses of Repetitive Motions in Goods to Person Order Picking Strategies Using Intelligent Human Factors System
Saed Talib Amer, Shaikha Al Shehhi, Nelson King, Jaby Mohammed

Chapter 19
Hybridization of IoT Networks with Intelligent Gateways
Neeti Gupta, Vidushi Sharma, Satish Penmatsa

Chapter 20
M/M1+M2/1/K Model for Monitoring Waiting Times via Intelligent Computing
R. Sivasamy, L. Gabaitiri, P.M. Kgosi, W. M. Thupeng

Erscheinungsdatum
Reihe/Serie Smart Technologies for Engineers and Scientists
Zusatzinfo 49 Tables, black and white; 81 Line drawings, black and white; 59 Halftones, black and white; 39 Illustrations, color; 101 Illustrations, black and white
Verlagsort London
Sprache englisch
Maße 156 x 234 mm
Themenwelt Informatik Weitere Themen CAD-Programme
Mathematik / Informatik Mathematik Angewandte Mathematik
Technik Elektrotechnik / Energietechnik
ISBN-10 1-032-47929-9 / 1032479299
ISBN-13 978-1-032-47929-3 / 9781032479293
Zustand Neuware
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