Title A Coral Reef Optimization Algorithm for Wave Height Time Series Segmentation Problems
Authors DURAN ROSAL, ANTONIO MANUEL, Guijo-Rubio, David , Antonio Gutierrez, Pedro , Salcedo-Sanz, Sancho , Hervas-Martinez, Cesar
External publication Si
Means Lect. Notes Comput. Sci.
Scope Proceedings Paper
Nature Científica
JCR Quartile 4
SJR Quartile 2
SJR Impact 0.29500
Publication date 01/01/2017
ISI 000443108200058
DOI 10.1007/978-3-319-59153-7_58
Abstract Time series segmentation can be approached using metaheuristics procedures such as genetic algorithms (GAs) methods, with the purpose of automatically finding segments and determine similarities in the time series with the lowest possible clustering error. In this way, segments belonging to the same cluster must have similar properties, and the dissimilarity between segments of different clusters should be the highest possible. In this paper we tackle a specific problem of significant wave height time series segmentation, with application in coastal and ocean engineering. The basic idea in this case is that similarity between segments can be used to characterise those segments with high significant wave heights, and then being able to predict them. A recently metaheuristic, the Coral Reef Optimization (CRO) algorithm is proposed for this task, and we analyze its performance by comparing it with that of a GA in three wave height time series collected in three real buoys (two of them in the Gulf of Alaska and another one in Puerto Rico). The results show that the CRO performance is better than the GA in this problem of time series segmentation, due to the better exploration of the search space obtained with the CRO.
Keywords Time series segmentation; Coral reef optimization; Genetic algorithms; Significant wave height time series
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