This book is a collection of best-selected research papers presented at the International Conference on Advances in Data-driven Computing and Intelligent Systems (ADCIS 2024) held at BITS Pilani, K Birla Goa Campus, Goa, India, during September 2021, 2024. It includes state-of-the-art research work in the cutting-edge technologies in the field of data science and intelligent systems. The book presents data-driven computing; it is a new field of computational analysis which uses provided data to directly produce predictive outcomes. The book is useful for academicians, research scholars, and industry persons.

Presents research papers on data-driven computing and intelligent systems Results of ADCIS 2024 held at BITS Pilani, K K Birla Goa Campus, Goa, India Serves as a reference for researchers and practitioners in academia and industry

Autorentext

Dr. Jagdish Chand Bansal is an Associate Professor (Senior Grade) at South Asian University New Delhi and a Visiting Professor at Maths and Computer Science, Liverpool Hope University UK. He also holds a visiting professorship at NIT Goa, India. Dr. Bansal obtained his Ph.D. in Mathematics from IIT Roorkee. Before joining SAU New Delhi, he worked as an Assistant Professor at ABV- Indian Institute of Information Technology and Management Gwalior and BITS Pilani. His primary areas of interest are swarm intelligence and nature-inspired optimization techniques. Recently, he proposed a fission-fusion social structure based optimization algorithm, Spider Monkey Optimization (SMO), which is being applied to various problems in the engineering domain. He has published over 70 research papers in various international journals/conferences. He is the Section Editor (editor-in-chief) of the journal MethodsX published by Elsevier. He is the series editor of the four Springer book series AIS, SADIC, ISTC and SST published by Springer. He is also the Associate Editor of Engineering Applications of Artificial Intelligence (EAAI) and ARRAY published by Elsevier. He is the general secretary of the Soft Computing Research Society (SCRS). He has also received Gold Medal at UG and PG levels.

Snehanshu Saha holds Master's Degree in Mathematical and Computational Sciences at Clemson University, USA and Ph.D. from the Department of Applied Mathematics at the University of Texas at Arlington in 2008. He was the recipient of the presitigious Dean's Fellowship during PhD and Summa Cum Laude for being in the top of the class. After working briefly at his Alma matter, Snehanshu moved to the University of Texas El Paso as a regular full-time faculty in the Department of Mathematical Sciences, University of Texas El Paso. Currently, He is a professor of Computer Science and Engineering at PES University since 2011 and heads the Center for AstroInformatis, Modeling and Simulation. He is also a visiting Professor at the department of Statistics, University of Georgia, USA and BTS Pilani, India. He has published 90 peer-reviewed articles in top-tier international journals and conferences and authored three text books on Differential Equations, Machine Learning and System Sciences respectively. Dr. Saha is an IEEE Senior member, ACM Senior Member, Vice Chair-International Astrostatistics Association and Chair, IEEE Computer Society0020Bangalore Chapter and Fellow of IETE. He's Editor of the Journal of Scientometric Research. Dr Saha is the recipient of PEACE Award for his foundational contributions in Machine Learning and AstroInformatics. Dr. Saha's current and future research interests lie in Data Science, Astronomy and theory of Machine Learning.

Carlos A. Coello Coello (Fellow, IEEE) received the Ph.D. degree in computer science from Tulane University, New Orleans, LA, USA, in 1996. He is currently a Professor with Distinction (CINVESTAV-3F Researcher), Computer Science Department, CINVESTAV-IPN, Mexico City, Mexico. He has authored and coauthored over 500 technical papers and book chapters. He has also co-authored the book Evolutionary Algorithms for Solving Multiobjective Problems (2nd ed., Springer, 2007) and has edited 3 more books with publishers such as World Scientific and Springer. His publications currently report over 60000 citations in Google Scholar (his H-index is 96). His major research interests are evolutionary multiobjective optimization and constraint-handling techniques for evolutionary algorithms. He has received several awards, including the National Research Award (in 2007) from the Mexican Academy of Science (in the area of exact sciences), the 2009 Medal to the Scientific Merit from Mexico City's congress, the Ciudad Capital: Heberto Castillo 2011 Award for scientists under the age of 45, in Basic Science, the 2012 Scopus Award (Mexico's edition) for being the most highly cited scientist in engineering in the 5 years previous to the award and the 2012 National Medal of Science in Physics, Mathematics and Natural Sciences from Mexico's presidency (this is the most important award that a scientist can receive in Mexico). He also received the Luis Elizondo Award from the Tecnológico de Monterrey in 2019. Additionally, he is the recipient of the 2013 IEEE Kiyo Tomiyasu Award, "for pioneering contributions to single- and multiobjective optimization techniques using bioinspired metaheuristics", of the 2016 The World Academy of Sciences (TWAS) Award in Engineering Sciences, and of the 2021 IEEE Computational Intelligence Society Evolutionary Computation Pioneer Award. Since January 2011, he is an IEEE Fellow. He is currently the Editor-in-Chief of the IEEE Transactions on Evolutionary Computation.

Hemant Rathore has completed his Bachelor of Engineering (B.E.) in computer science from RGTU, followed by Master of Engineering (M.E) in software systems and Doctor of Philosophy (Ph.D.) from BITS Pilani. He is currently working as an Assistant Professor in the Department of CS & IS, BITS Pilani, K K Birla Goa Campus, India. He has strong academic and industry research experience in the field of data science. His current research interests are in the area of machine learning and deep learning, specifically adversarial robustness, explainability, and interpretability. He has published many research papers in various top journals. He has taught and likes to teach courses like Machine Learning, Advanced Data Mining, Data Mining, and Network Security to undergraduate and postgraduate students. He has also guided numerous students for short-term various projects.

Inhalt

Unveiling Patterns in Social Media Interactions Recurrent Neural Networks for Deep Learning Behavioral Analysis.- Evaluating Machine Learning and Deep Learning Models for Sentiment Analysis of Farmers Protests on Twitter.- Analyzing the Impact of Attenuation Coefficient in DCF Compensated RoF System using Different RF Signals.- A Comparative Study of Bloodstain Pattern Analysis on Different Types of Paper Surfaces.- Decentralized Distributed Financial Audit System.