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Advanced extreme learning machines vs. deep learning models for peak wave energy period forecasting: A case study in Queensland, Australia
journal contribution
posted on 2021-01-01, 00:00 authored by Mumtaz Ali, Ramendra Prasad, Yong XiangYong Xiang, Adarsh Sankaran, Ravinesh C Deo, Fuyuan Xiao, Shuyu ZhuThe peak period of an energy-generating wave is one of the most important parameters that describe the spectral shape of the oceanic wave, as this indicates the duration for which the waves prevail with respect to their maximum extractable energy. In this paper, a half-hourly peak wave energy period (TP) forecast model is constructed using a suite of statistically significant lagged inputs based on the partial auto-correlation function with an extreme learning machine model developed and its predictive utility is benchmarked against deep learning models, i.e., convolutional neural network (CNN/CovNet) and recurrent neural network (RNN) models and other traditional M5tree, Conditional Maximization based Multiple Linear Regression (MLR-ECM) and MLR models. The objective model (ELM) vs. the comparison models (CNN, RNN, M5tree, MLR-ECM, and MLR) were trained and validated independently on the test dataset obtained from coastal zones of eastern Australia that have a high potential for implementation of wave energy generation systems. The outcomes ascertain that the ELM model can generate significantly accurate predictions of the half-hourly peak wave energy period, providing a good level of accuracy relative to deep learning models in selected coastal study zones. The study establishes the practical usefulness of the ELM model as being a noteworthy methodology for the applications in renewable and sustainable energy resource management systems.
History
Journal
Renewable EnergyVolume
177Pagination
1031 - 1044Publisher
ElsevierLocation
Amsterdam, The NetherlandsPublisher DOI
ISSN
0960-1481Language
engPublication classification
C1 Refereed article in a scholarly journalUsage metrics
Keywords
deep learningRNNCNNELMPeak wave energy periodCoastal WavesScience & TechnologyTechnologyGreen & Sustainable Science & TechnologyEnergy & FuelsScience & Technology - Other TopicsSUPPORT VECTOR MACHINENEURAL-NETWORKSSOLAR-RADIATIONMAXIMUM-LIKELIHOODPAN EVAPORATIONPREDICTIONHEIGHTALGORITHMENSEMBLERIVERMechanical Engineering
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