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Abstract Amid escalating climate change and energy crises, wind energy, as a pivotal renewable resource, poses significant challenges to grid stability and energy management due to its inherent stochastic intermittency and nonlinear dynamics. Consequently, this research presents a hybrid prediction system, ICEEMDAN-NCRBMO-AELM, integrating data decomposition with intelligent computing to reveal spatiotemporal coupling patterns in climatic variables for reliable wind power forecasting.
As a journalist, you can create a free Muck Rack account to customize your profile, list your contact preferences, and upload a portfolio of your best work.
