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Integrated Quantum Computing and Machine Intelligence for Sustainable Energy Solutions
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Author(s): Muthuraman Subbiah (University of Technology and Applied Sciences, Oman), R. V. V. Krishna (Aditya College of Engineering and Technology, Jawaharlal Nehru Technological University, Kakinada, India), V. Satyanarayana (Aditya College of Engineering and Technology, Jawaharlal Nehru Technological University, Kakinada, India)and Abhinav Kataria (Christ University, India)
Copyright: 2024
Pages: 12
Source title:
Real-World Challenges in Quantum Electronics and Machine Computing
Source Author(s)/Editor(s): Christo Ananth (Samarkand State University, Uzbekistan), T. Ananth Kumar (IFET College of Engineering, India)and Osamah Ibrahim Khalaf (Al-Nahrain University, Iraq)
DOI: 10.4018/979-8-3693-4001-1.ch007
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Abstract
The synergistic integration of amount computing and machine intelligence to address challenges in sustainable energy results. By using the computational power of amount computing and the adaptive literacy capabilities of machine intelligence, the study aims to optimize energy product, distribution, and application in a sustainable manner. Through advanced algorithms and optimisation ways, the exploration explores how intertwined amount computing and machine intelligence can enhance the effectiveness, trustability, and environmental sustainability of energy systems. The findings offer perceptivity into the eventuality of this interdisciplinary approach to revise the energy sector, paving the way for the development of innovative results for renewable energy integration, smart grid operation, and energy-effective technologies. Eventually, the exploration contributes to the advancement of sustainable energy results by employing the combined power of amount computing and machine intelligence to address complex challenges in energy optimisation and resource operation.
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