Mathematical Modeling, Computational Intelligence Techniques and Renewable Energy

Proceedings of the Fifth International Conference, MMCITRE 2025
Erscheinungsjahr 2027
ISBN: 978-3-032-32752-9
Verlag: Springer Nature Switzerland AG

Buch, Englisch, 615 Seiten, Format (B × H): 155 mm x 235 mm

Reihe: Lecture Notes in Networks and Systems

The book is a collection of best-selected research papers presented at the Fifth International Conference on “Mathematical Modeling, Computational Intelligence Techniques and Renewable Energy (MMCITRE 2025),” organized by International Institute of Information Technology, Naya Raipur (IIIT-NR), Chhattisgarh, India. This book presents new knowledge and recent developments in all aspects of computational techniques, mathematical modeling, energy systems, applications of fuzzy sets, and intelligent computing. This book provides innovative works of researchers, academicians, and students in the area of interdisciplinary mathematics, statistics, computational intelligence, and renewable energy.

Zielgruppe

Research

Autoren/Hrsg.

Sahni, Manoj

Merigó, José M.

León-Castro, Ernesto

Kumar Chaube, Mithilesh

Shekhar Nishad, Chandra

Fachgebiete

• Technische Wissenschaften Energietechnik | Elektrotechnik Alternative und erneuerbare Energien
• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Maschinelles Lernen

Inhaltsverzeichnis

A Review of Solutions using Generative Adversarial Networks in Medical Imaging for Lumbar Spine.- Ai And IOT Enabled Predictive Energy Management for Renewable Energy Conversion Systems.- AutoREAD A Retrieval Augmented Pipeline for README Generation
Ensemble Based Zero Day Detection using Host Memory Analysis.- ScrumBench and Jason Mack Scaling Agentic AI for Automation in Agile Software Teams.- Machine Learning Driven Energy Auditing and Climate Resilient Agricultural Modeling Using IOT Integrated Frameworks.- Higher order Statistical Features based Machine Learning Approach for Evaluating Advertisement Effectiveness through Eye Tracking Data Analysis.- A Review Disease Detection in Plants Using Machine Learning Technique.

Über Autor(innen)

Dr. Manoj Sahni is a dedicated and experienced Mathematics teacher and researcher with more than 20 years of experience and currently serving as a Professor in the Department of Mathematics, School of Technology, Pandit Deendayal Energy University, Gandhinagar, Gujarat, India. He has published more than 120 research papers in peer-reviewed Journals (SCI/ SCIE/ Scopus), Conference Proceedings (Scopus Indexed) with reputed publishers like Springer, Elsevier, Taylor and Francis, and many more. He also serves as an Advisory board member, and Reviewer for many international journals of repute. He has organized four International Conferences on MMCITRE in 2020, 21, 22 and 24 respectively.

Prof. José M. Merigó Lindahl is a Professor at the School of Information, Systems & Modelling at the Faculty of Engineering and Information Technology at the University of Technology Sydney (Australia) He has published more than 500 articles in journals, books and conference proceedings, including journals such as Information Sciences, IEEE Computational Intelligence Magazine, IEEE Transactions on Fuzzy Systems, European Journal of Operational Research, Expert Systems with Applications, International Journal of Intelligent Systems, Applied Soft Computing, Computers & Industrial Engineering and Knowledge-Based Systems. He has also published several books with Springer and with World Scientific.

Dr. Ernesto Leon Castro is an Associate Professor at Universidad Católica de la Santísima Concepcion (Chile) and Instituto Tecnológico de Sonora (México). PhD in Administrative Sciences from Universidad de Occidente (Mexico). Member of the National System of Researchers (Level 1). Within his research areas are aggregation operators, decision making, innovation, finance, fuzzy logic and other related topics. He has numerous publications in different journals indexed in the Web of Science / Scopus and has participated in different international conferences. He is part of the Ibero-American Network for Competitiveness, Innovation and Development (REDCID) and is a member of the Business Studies in Uncertain Environments research group.

Dr. Mithilesh Kumar Chaube is currently working as an Associate Professor in the Department of Science and Mathematics at IIIT Naya Raipur. Prior to join IIIT Naya Raipur, he was an Assistant Professor in the Department of Mathematics at Echelon Institute of Technology Faridabad, Galgotias University Greater Noida and RKGIT Ghaziabad, India. He has completed M.Sc. (Mathematics) from Harish Chandra PG College Varanasi in 2005. He completed his Ph.D. degree in Applied Mathematics from IIT BHU under the supervision of Prof. S. K. Pandey in February 2011. He has published more than 55 research papers in journals and conference proceedings of international repute.

Dr. Chandra Shekhar Nishad is currently working as an Assistant Professor in the Department of Science and Mathematics since July 03, 2023. Prior to joining IIIT-NR, he was an Assistant Professor in the Department of Mathematics, School of Technology, Pandit Deendayal Energy University (PDEU) Gandhinagar, India. He has completed M.Sc. (Mathematics & Computing) from IIT Guwahati in 2009 and M.Tech. (Industrial Mathematics & Scientific Computing) from IIT Madras in 2012. He completed his Ph.D. degree in Applied Mathematics from IIT Kharagpur under the supervision of Prof. G.P Raja Sekhar in July 2019. He has received DAAD Scholarship (DAAD IIT Master Sandwich Program) for doing M.Tech. Dissertation at Technical University Darmstadt Germany in 2011. He has published more than 35 research papers in journals and conference proceedings of international repute.