A novel hybrid algorithm based on Empirical Fourier decomposition and deep learning for wind speed forecasting

B Kumar, N Yadav - Energy Conversion and Management, 2024 - Elsevier
As the demand for renewable energy is increasing, wind speed forecasting (WSF) becomes
increasingly popular and essential for wind power generation. Several methods have been …

An efficient forecasting method for time series based on visibility graph and multi-subgraph similarity

Y Hu, F **ao - Chaos, Solitons & Fractals, 2022 - Elsevier
Recently network-based method for forecasting time series has become a hot research
topic. Although some methods have been recognized for their prediction performance, how …

Etemadi regression in chemometrics: Reliability-based procedures for modeling and forecasting

S Etemadi, M Khashei - Heliyon, 2024 - cell.com
The creation of predictive models with a high degree of generalizability in chemical analysis
and process optimization is of paramount importance. Nonetheless, formulating a prediction …

A novel framework for direct multistep prediction in complex systems

T Wu, F An, X Gao, W Zhong, J Kurths - Nonlinear Dynamics, 2023 - Springer
Multistep prediction is an open challenge in many real-world systems for a long time.
Despite the advantages of previous approaches, eg, step-by-step iteration, they have some …

Discrete learning-based intelligent methodology for heart disease diagnosis

M Khashei, N Bakhtiarvand - Biomedical Signal Processing and Control, 2023 - Elsevier
Classification is one of the most frequently used data mining approaches which has been
broadly applied in different fields of sciences, such as engineering, finance, energy …