Ricky, S.K. and Rahim, L.A. (2021) Metocean Prediction using Hadoop, Spark R. In: UNSPECIFIED.
Full text not available from this repository.Abstract
This project is the development of an analysis system for historical Metocean Data. It is a single page reactive web application with shiny web UI package of R containing forecasting model, ARIMA and two ML algorithms, Linear Regression and H2O AutoML developed with R for the variables of Metocean data stored in HDFS of a virtual Hadoop cluster and spark is integrated to make the computations happen in-memory. The predictions is compared to the actual data to see its correctness with RMSE. Performance difference of the application deployed on desktop and on the server is also discussed. The application performs better when running in the server than on desktop. © 2021 IEEE.
Item Type: | Conference or Workshop Item (UNSPECIFIED) |
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Additional Information: | cited By 1; Conference of 6th International Conference on Computer and Information Sciences, ICCOINS 2021 ; Conference Date: 13 July 2021 Through 15 July 2021; Conference Code:170762 |
Uncontrolled Keywords: | Artificial intelligence; Computer science; Computers; Software engineering, Analysis system; Forecasting modeling; Metocean; Ml algorithms; Running-in; WEB application, Forecasting |
Depositing User: | Mr Ahmad Suhairi UTP |
Date Deposited: | 10 Nov 2023 03:29 |
Last Modified: | 10 Nov 2023 03:29 |
URI: | https://khub.utp.edu.my/scholars/id/eprint/14710 |