 A Coral Reefs Optimization algorithm with Harmony Search operators for accurate wind speed predictionS. Salcedo-Sanz, A. Pastor-Sánchez, J. Del Ser, L. Prieto and Z.W. Geem Renewable Energy, 2015, vol. 75, issue C, 93-101 Abstract: This paper introduces a new hybrid bio-inspired solver which combines elements from the recently proposed Coral Reefs Optimization (CRO) algorithm with operators from the Harmony Search (HS) approach, which gives rise to the coined CRO-HS optimization technique. Specifically, this novel bio-inspired optimizer is utilized in the context of short-term wind speed prediction as a means to obtain the best set of meteorological variables to be input to a neural Extreme Learning Machine (ELM) network. The paper elaborates on the main characteristics of the proposed scheme and discusses its performance when predicting the wind speed based on the measures of two meteorological towers located in USA and Spain. The good results obtained in these experiments when compared to naïve versions of the CRO and HS algorithms are promising and pave the way towards the utilization of the derived hybrid solver in other optimization problems arising from diverse disciplines. Keywords: Short term wind speed prediction; Feature selection; Coral Reefs Optimization; Harmony Search; Extreme learning machines (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:eee:renene:v:75:y:2015:i:c:p:93-101 DOI: 10.1016/j.renene.2014.09.027 Access Statistics for this article Renewable Energy is currently edited by Soteris A. Kalogirou and Paul Christodoulides More articles in Renewable Energy from Elsevier |
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