首页|Hong Kong Polytechnic University Researcher Provides Details of New Studies and Findings in the Area of Machine Learning (Advancements and Future Directions in the Application of Machine Learning to AC Optimal Power Flow: A Critical Review)
Hong Kong Polytechnic University Researcher Provides Details of New Studies and Findings in the Area of Machine Learning (Advancements and Future Directions in the Application of Machine Learning to AC Optimal Power Flow: A Critical Review)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-New study results on artificial intell igence have been published. According to news reporting originating from Hong Ko ng, People's Republic of China, by NewsRx correspondents, research stated, "Opti mal power flow (OPF) is a crucial tool in the operation and planning of modern p ower systems." Funders for this research include The Hong Kong Polytechnic University. Our news reporters obtained a quote from the research from Hong Kong Polytechnic University: "However, as power system optimization shifts towards larger-scale frameworks, and with the growing integration of distributed generations, the com putational time and memory requirements of solving the alternating current (AC) OPF problems can increase exponentially with system size, posing computational c hallenges. In recent years, machine learning (ML) has demonstrated notable advan tages in efficient computation and has been extensively applied to tackle OPF ch allenges."
Hong Kong Polytechnic UniversityHong K ongPeople's Republic of ChinaAsiaCyborgsEmerging TechnologiesMachine L earning
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