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Quantum Long Short-Term Memory (QLSTM) vs Classical LSTM in Time Series Forecasting: A Comparative Study in Solar Power Forecasting
April 10, 2024, 4:43 a.m. | Saad Zafar Khan, Nazeefa Muzammil, Salman Ghafoor, Haibat Khan, Syed Mohammad Hasan Zaidi, Abdulah Jeza Aljohani, Imran Aziz
cs.LG updates on arXiv.org arxiv.org
Abstract: Accurate solar power forecasting is pivotal for the global transition towards sustainable energy systems. This study conducts a meticulous comparison between Quantum Long Short-Term Memory (QLSTM) and classical Long Short-Term Memory (LSTM) models for solar power production forecasting. The primary objective is to evaluate the potential advantages of QLSTMs, leveraging their exponential representational capabilities, in capturing the intricate spatiotemporal patterns inherent in renewable energy data. Through controlled experiments on real-world photovoltaic datasets, our findings reveal …
abstract arxiv comparison cs.lg energy forecasting global long short-term memory lstm memory pivotal power quant-ph quantum series solar solar power solar power forecasting study sustainable sustainable energy systems time series time series forecasting transition type
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