{"title":"Wind Wave Prediction by using Autoregressive Integrated Moving Average model : Case Study in Jakarta Bay","authors":"D. Adytia, Alif Rizal Yonanta, N. Subasita","doi":"10.21108/IJOICT.2018.42.300","DOIUrl":null,"url":null,"abstract":"Prediction of wind wave is highly needed to support safe navigation, especially for ship. Besides that, loading and unloading activities in a harbour, as well as for design purpose of coastal and offshore structures, data of prediction of wave height are needed. Based on its nature, the wind wave has random behaviour that is highly depending on behaviour of wind as the main driving force. In this paper, we propose a prediction method for wind wave by using Autoregressive Integrated Moving Average or ARIMA. To obtain historical data of wind wave, we perform wave simulation by using a phase-averaged wave model SWAN (Simulating Wave Near Shore). From the simulation, time series of wind wave is obtained. The prediction of wind wave is performed to calculate forecast of 24 hours ahead. Here, we perform wind wave prediction in a location in Jakarta Bay, Indonesia. We perform several combination of ARIMA model to obtain best fit model for wind wave prediction in the location in Jakarta Bay. Results of prediction show that ARIMA model give an accurate prediction especially for short term prediction.","PeriodicalId":137090,"journal":{"name":"International Journal on Information and Communication Technology (IJoICT)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-04-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal on Information and Communication Technology (IJoICT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.21108/IJOICT.2018.42.300","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3
Abstract
Prediction of wind wave is highly needed to support safe navigation, especially for ship. Besides that, loading and unloading activities in a harbour, as well as for design purpose of coastal and offshore structures, data of prediction of wave height are needed. Based on its nature, the wind wave has random behaviour that is highly depending on behaviour of wind as the main driving force. In this paper, we propose a prediction method for wind wave by using Autoregressive Integrated Moving Average or ARIMA. To obtain historical data of wind wave, we perform wave simulation by using a phase-averaged wave model SWAN (Simulating Wave Near Shore). From the simulation, time series of wind wave is obtained. The prediction of wind wave is performed to calculate forecast of 24 hours ahead. Here, we perform wind wave prediction in a location in Jakarta Bay, Indonesia. We perform several combination of ARIMA model to obtain best fit model for wind wave prediction in the location in Jakarta Bay. Results of prediction show that ARIMA model give an accurate prediction especially for short term prediction.
风浪预报是保障船舶安全航行的重要手段。此外,港口内的装卸活动以及沿海和近海结构物的设计都需要海浪高度的预测数据。基于其性质,风波具有随机行为,高度依赖于作为主要驱动力的风的行为。本文提出了一种基于自回归综合移动平均(ARIMA)的风浪预测方法。为了获得风浪的历史数据,我们采用相位平均波浪模型SWAN (simulation wave Near Shore)进行了波浪模拟。仿真得到了风浪的时间序列。进行了风浪预报,计算了24小时的预报。在这里,我们在印度尼西亚雅加达湾的一个地方进行风浪预测。对ARIMA模型进行了多次组合,得到了雅加达湾地区风浪预报的最佳拟合模型。预测结果表明,ARIMA模型具有较好的预测精度,特别是短期预测。