{"title":"实时预测海浪的人工智能工具","authors":"Pooja Jain, M. Deo","doi":"10.2174/1874835X00801010013","DOIUrl":null,"url":null,"abstract":"Prediction of wind generated ocean waves over short lead times of the order of some hours or days is helpful in carrying out any operation in the sea such as repairs of structures or laying of submarine pipelines. This paper discusses an application of different artificial intelligent tools for this purpose. The physical domain where the wave forecasting is made belongs to the western part of the Indian coastline in Arabian Sea. The tools used are artificial neural networks, ge- netic programming and model trees. Station specific forecasts are made at those locations where wave data are continu- ously observed. A time series forecasting scheme is employed. Based on a sequence of preceding observations forecasts are made over lead times of 3 hr to 72 hr. Large differences in the accuracy of the forecasts were not seen when alternative forecasting tools were employed and hence the user is free to use any one of them as per her convenience and confidence. A graphical user interface has been developed that operates on the received wave height data from the field and produces the forecasts and further makes them accessible to any user located anywhere in the world.","PeriodicalId":206173,"journal":{"name":"The Open Ocean Engineering Journal","volume":"20 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2008-08-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"41","resultStr":"{\"title\":\"Artificial Intelligence Tools to Forecast Ocean Waves in Real Time\",\"authors\":\"Pooja Jain, M. Deo\",\"doi\":\"10.2174/1874835X00801010013\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Prediction of wind generated ocean waves over short lead times of the order of some hours or days is helpful in carrying out any operation in the sea such as repairs of structures or laying of submarine pipelines. This paper discusses an application of different artificial intelligent tools for this purpose. The physical domain where the wave forecasting is made belongs to the western part of the Indian coastline in Arabian Sea. The tools used are artificial neural networks, ge- netic programming and model trees. Station specific forecasts are made at those locations where wave data are continu- ously observed. A time series forecasting scheme is employed. Based on a sequence of preceding observations forecasts are made over lead times of 3 hr to 72 hr. Large differences in the accuracy of the forecasts were not seen when alternative forecasting tools were employed and hence the user is free to use any one of them as per her convenience and confidence. A graphical user interface has been developed that operates on the received wave height data from the field and produces the forecasts and further makes them accessible to any user located anywhere in the world.\",\"PeriodicalId\":206173,\"journal\":{\"name\":\"The Open Ocean Engineering Journal\",\"volume\":\"20 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2008-08-22\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"41\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"The Open Ocean Engineering Journal\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.2174/1874835X00801010013\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"The Open Ocean Engineering Journal","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2174/1874835X00801010013","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Artificial Intelligence Tools to Forecast Ocean Waves in Real Time
Prediction of wind generated ocean waves over short lead times of the order of some hours or days is helpful in carrying out any operation in the sea such as repairs of structures or laying of submarine pipelines. This paper discusses an application of different artificial intelligent tools for this purpose. The physical domain where the wave forecasting is made belongs to the western part of the Indian coastline in Arabian Sea. The tools used are artificial neural networks, ge- netic programming and model trees. Station specific forecasts are made at those locations where wave data are continu- ously observed. A time series forecasting scheme is employed. Based on a sequence of preceding observations forecasts are made over lead times of 3 hr to 72 hr. Large differences in the accuracy of the forecasts were not seen when alternative forecasting tools were employed and hence the user is free to use any one of them as per her convenience and confidence. A graphical user interface has been developed that operates on the received wave height data from the field and produces the forecasts and further makes them accessible to any user located anywhere in the world.