Скачать с ютуб Automated deep learning based-design for solving time series forecasting problems в хорошем качестве

Automated deep learning based-design for solving time series forecasting problems

Abstract: Accurate prediction of solar energy is an important issue for photovoltaic power plants to enable early participation in energy auction industries and cost-effective resource planning. This article introduces a new deep learning-based multistep ahead approach to improve the forecasting performance of global horizontal irradiance (GHI). A deep convolutional long short-term memory is used to extract optimal features for the accurate prediction of the GHI. The performance of such deep neural networks directly depends on their architectures. To deal with this problem, a swarm evolutionary optimization method, called the sine-cosine algorithm, is applied and advanced to automatically optimize the network architecture. A three-phase modification model is proposed to increase the diversity of the population and avoid premature convergence in the optimization mechanism. The performance of the proposed method is investigated using three datasets collected from three solar stations in the east of the United States. The experimental results demonstrate the superiority of the proposed method in comparison to other forecasting models. Speakers: Dr Seyed Mohammad Jafar Jalali, Deakin University, Australia Speaker’s Bio: Seyed Mohammad Jafar Jalali (Member, IEEE) received his M.S. degree in Information Technology major in Advanced Information Systems from Allameh Tabataba'i Universit, Tehran, Iran in 2016 and his PhD with the Institute for Intelligent Systems Research and Innovation (IISRI), Deakin University, VIC, Australia in 2021. He was also a research assistant at the University of Massachusetts, MA, USA, conducting research in the field of artificial intelligence. His primary research interests include machine learning, deep neural architecture search, deep learning, and optimization. Dr Jalali received the prestigious Deakin University Postgraduate Research Scholarship (DUPRS) in 2018. Besides, he is the winner of the prestigious Alfred Deakin Postdoctoral Research Fellowship award in the year 2021. He is currently a research fellow at Deakin University, VIC, Australia.