{"title":"Prediction of significant wave height in The Java Sea using Artificial Neural Network","authors":"I. Rizianiza, A. S. Aisjah","doi":"10.1109/ISITIA.2015.7219944","DOIUrl":null,"url":null,"abstract":"The Java Sea is one of the busiest ship traffic both of domestic and international shipping and potential marine accident is quite high. It is about 43.6% of marine accidents is caused by natural factor. There are two point in this research. Point 1 at latitude 5° 55'29.03\" S longitude 110°51'42.88\" E and point 2 at latitude 4°39'41.99\" S longitude 109°10'7.15\" E. Design predictor of significant wave height is using Artificial Neural Network with backpropagation algorithm. The predictor consists of three inputs. They are significant wave height (m); wind speed (m/s) and wind direction (degree). Architecture of Artificial Neural Network is point 1 [3, 6, 1] dan point 2 [3, 3, 1]. The result RMSE in this prediction are point 1 0.006 m; point 2 0.075 m.","PeriodicalId":124449,"journal":{"name":"2015 International Seminar on Intelligent Technology and Its Applications (ISITIA)","volume":"118 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"9","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 International Seminar on Intelligent Technology and Its Applications (ISITIA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISITIA.2015.7219944","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 9
Abstract
The Java Sea is one of the busiest ship traffic both of domestic and international shipping and potential marine accident is quite high. It is about 43.6% of marine accidents is caused by natural factor. There are two point in this research. Point 1 at latitude 5° 55'29.03" S longitude 110°51'42.88" E and point 2 at latitude 4°39'41.99" S longitude 109°10'7.15" E. Design predictor of significant wave height is using Artificial Neural Network with backpropagation algorithm. The predictor consists of three inputs. They are significant wave height (m); wind speed (m/s) and wind direction (degree). Architecture of Artificial Neural Network is point 1 [3, 6, 1] dan point 2 [3, 3, 1]. The result RMSE in this prediction are point 1 0.006 m; point 2 0.075 m.