Hourly and daily prediction of sea wave height In the Chabahar area

Document Type : Research Article

Authors

1 PhD. Candidate in Water Resources Engineering, Department of Hydrology and Water Resources, Faculty of Water Sciences Engineering, Shahid Chamran University of Ahvaz, Ahvaz, Iran

2 Assistant professor of Water Engineering, Department of Hydrology and Water Resources, Faculty of Water Sciences Engineering, Shahid Chamran University of Ahvaz, Iran.

Abstract

The waves is important, because of it’s energy and high impact in maritime activities. Considering the effect of wave on marine activities in Chabahar, different factors influencing the wave height were considered in the present study. In this paper, the Wolf Search Algorithm (WSA) was used to predicting wave height in two categories, daily and hourly. For this purpose, the daily data of the year 2007-2011 and hourly data consisting of two month data of the year 2006 were employed. The results of the WSA were compared with Genetic Algorithm (GA) and Harmony Search Algorithm (HS). The WSA had a better performance for both hourly and daily data. So that R2, RMSE, d And MAE predict 0.9497, 0.0704, 0.987 and 0.0483 for hourly prediction and 0.8558, 0.1742, 0.9599 and 0.1138 for daily prediction respectively. The results show the high ability of evolutionary algorithms in wave height prediction in this Region.

Keywords

Main Subjects


[1]. Derakhshan S, Gharabaghi A, Chenaghlu MR. Prediction of sea waves specification by experimental methods in Bushehr. 1st national congrees on civil engineering. Sharif University. Tehran. 2004; 1-9. [Persian]
[2]. Khalili N. Forecasting precipitation with artificial neural networks. M.Sc Thesis. Water engineering Department. Ferdowsi university of Mashhad. 2006; [Persian]
[3]. Lari K, Pourmandi-Yekta A, Mehdipour F. Wind waves prediction by the statistical model based on neural network in Bushehr Province. 4thinternational conference on coasts. port and marine structures. Bandar Abbas. 2000; 1-7. [Persian]
[4]. Pierson WJ, Moskowitz L. A proposed spectral form for fully developed wind seas based on the similarity theory of SA Kitaigorodskii. Journal of geophysical research. 1964; 69(24):5181-5190.
[5]. Hasselmann K, Barnett TP, Bouws E, Carlson H, Cartwright DE, Enke K, et al. Measurements of wind-wave growth and swell decay during the Joint North Sea Wave Project (JONSWAP). Research project. Deutsches Hydrographisches Institut; 1973.p. 7-91.
[6]. Imani H, Kamranzadeh B. Scrutiny results of numerical simulation significant wave height in Chabahar. Sixth International Conference on Offshore Industries. Iranian Offshore Engineering Society. Tehran. 2015; 1-8. [Persian]
[7]. Zhang S, Song Z, Li Y. An advanced inversion algorithm for significant wave height estimation based on random field. Ocean Engineering. 2016; 15(127):298-304.
[8]. Taleghani M, Amirteymuri AR. Wave height predicted in Caspian Sea using artificial neural networks. Journal of Operational Research in Its Applications (Applied Mathematics). 2008; 5(18):39-47. [Persian]
[9]. Zamani A, Azimian A. Wave height prediction in Caspian Sea by neural network. 9th conference of Fluid dynamics. Shiraz University. 2004; 1-11. [Persian]
[10]. Abed-Elmdoust A, Kerachian R. Wave height prediction using the rough set theory. Ocean Engineering. 2012; 1(54):244-250.
[11]. Amani-Dashlejeh J, Bonakdar, L. Using neural network in prediction of wave height and period with different return period in South Bandar Abbas. 10th Marine industries conference. Khoramshahr. 2008; 1-11. [Persian]
[12]. Krishna Kumar N, Savitha R, Al Mamun A. Regional ocean wave height prediction using sequential learning neural networks. Ocean Engineering. 2017; 1(129):605-612.
[13]. Edalatpanah F, Rezazadeh P. Prediction of wave parameters by SWAN model. 12th conference of Fluid dynamics.Nushirvani University of Babol. 2009; 1-14. [Persian]
[14]. Pournemat-Roudsari A, Qaderi K, Bakhtiari B, Ahmadi MM. Wave height prediction in Caspian Sea by GMDH. National conference of sea water utilization.Kerman; 2011.P. 659-666. [Persian]
[15]. Mohammadrezapour-Tabari M, Soltani J. The stream flow prediction model using Fuzzy inference system and particle swarm optimization. Water and wastewater consulting engineers research development. 2013; 24:112-124. [Persian]
[16]. Haghighi H. Hydrology and hydrobiology of Chabahar gulf. Research project. Iranian Fisheries Science Research Institute.; 1995.p. 5-12. [Persian]
[17]. Shirinmanesh S, Chegini V. Study estimated recoverable energy from wave and tidal flow in Chabahar bay. Journal of Khoramshahr Marine Scinence and Technology. 2011; 10(2):91-107. [Persian]
 [18]. Tang R, Fong S, Yang XS, Deb S. Wolf search algorithm with ephemeral memory. InDigital Information Management (ICDIM). Seventh International Conference; 2012.p. 165-172. IEEE.
[19]. Willmott CJ. On the validation of models. Physical geography. 1981; 2(2):184-94.