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TOPICAL COLLECTIONS

Next-Generation Decision-Making Systems for Advancing Eco-Friendly Energy Solutions
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Guest Editors

Dr. V. B. Murali Krishna

Dr. V. B. Murali Krishna

Department of Electrical Engineering, National Institute of Technology-Andhra Pradesh

Dr. V. B. Murali Krishna is a certified Chartered Engineer (CEng) from The Institution of Engineers (India). He has a doctorate in electrical engineering from the Central University of Karnataka. Currently, he is part of the teaching faculty at the National Institute of Technology-Andhra Pradesh (NIT-Andhra Pradesh), India.Beyond his academic and research activities, Dr. Krishna holds multiple editorial roles, including associate editor at e-Prime - Advances in Electrical Engineering, Electronics and Energy and topical editor at Contemporary Mathematics. He is also an editorial board member for Discover Energy. An active reviewer for over 25 international journals and five conference series, he has received the Reviewer of Excellence award. His research has earned three Best Paper awards at international conferences, and his PhD thesis received the Best Thesis award from IEEE Bangalore. Additionally, he has organized three national conferences, chaired sessions at international conferences (2023–24), and has over 50 published or presented academic articles.His research focuses on renewable energy, smart grids, electric vehicles, IoT, adaptive technologies, system optimization, and AI-driven data analysis.

Rajesh Cheruku

Rajesh Cheruku

School of Engineering, Dayananda Sagar University

Dr. Rajesh Cheruku has a doctorate in physics from Pondicherry University, India. Starting in 2015, he held the position of assistant professor at Yeungnam University in South Korea, where he continued to work until 2020. In 2021, he was appointed assistant professor at the Central University of Karnataka, India. Since 2022, he has been an assistant professor at Dayananda Sagar University, India. Dr. Cheruku serves as a reviewer for several prestigious journals and has published more than 45 academic articles. His interests include system control, security, and optimization in renewable energy, battery storage, EV charging, smart alerts, and IoT-driven renewable adaptive technologies.

İskender Akkurt

İskender Akkurt

Suleyman Demirel University

Dr. İskender Akkurt is a professor at the Faculty of Engineering and Natural Sciences, Department of Physics at Süleyman Demirel University, Turkey. He received his doctorate from the University of Glasgow in 1998. He has published over 160 articles in reputed international journals, presented more than 50 papers at international scientific meetings, contributed to conference proceedings, and authored two books.

Kenneth E. Okedu

Kenneth E. Okedu

School of Information Technology and Engineering, Melbourne Institute of Technology

Dr. Kenneth Okedu is a researcher and professor specializing in renewable energy and power systems. He earned his PhD from the Kitami Institute of Technology, Japan, and was a research fellow in the Department of Electrical and Computer Engineering at MIT, USA. He has held academic and visiting faculty positions in Nigeria, Oman, and Turkey. A prolific researcher, Dr. Okedu serves as an editor for multiple engineering journals and was recognized as a top 1% peer reviewer in Engineering by Publons. He was also among Stanford University's top 2% of most cited researchers globally. Currently, he is a researcher at Victoria University, Melbourne, and a faculty member at the Melbourne Institute of Technology. In addition, he works full-time as a Renewable and Power Systems Advisor at Vysus Group, Melbourne, Australia. His research focuses on power system stability, wind energy integration, and renewable energy storage.

Collection Overview

As the globe faces rising environmental difficulties, the switch to sustainable energy solutions has become more crucial than ever. Data-driven decision-making systems play a vital role in promoting eco-friendly energy solutions by enhancing the efficiency, accuracy, and adaptability of modern energy infrastructures. These models encourage innovation in sustainable energy development by leveraging cutting-edge technologies such as artificial intelligence, machine learning, deep learning, cybersecurity, smart sensing, image processing, control and optimization, energy management systems, and smart grids. Furthermore, the seamless integration of locally accessible renewable energy sources into electric vehicles via smart grids stimulates community-driven energy solutions and promotes energy fairness. 

This Methods Collection intends to study developing decision-making frameworks to assist green energy systems and sustainable development. By addressing critical research gaps, the collection introduces new methodologies and applications that refine decision-making processes essential for the growth of sustainable energy solutions.

Articles

Modeling a Novel Self-Optimized Wolf Optimizer for a Heterogeneous Network Model for Energy and Node Lifetime Analysis

Modeling a Novel Self-Optimized Wolf Optimizer for a Heterogeneous Network Model for Energy and Node Lifetime Analysis

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2025

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Abstracts

Characterizing multiphase flow in porous media by polynomial physical neural network

Yunqi Jiang1

1Petrochina Southwest Oil and Gas Field Company