Metocean Prediction using Hadoop, Spark & R
This project is the development of an analysis system for historical Metocean Data. it is also partial recreation of a previous system overcoming some of its shortcomings. The new system will be a single page reactive web application with shiny web UI containing forecasting model, ARIMA developed wi...
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Online Access: | http://utpedia.utp.edu.my/20962/1/SUMAYEMA%20KABIR%20RICKY_24802.pdf http://utpedia.utp.edu.my/20962/ |
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my-utp-utpedia.209622021-09-10T08:57:46Z http://utpedia.utp.edu.my/20962/ Metocean Prediction using Hadoop, Spark & R Sumayema, Kabir Ricky Q Science (General) This project is the development of an analysis system for historical Metocean Data. it is also partial recreation of a previous system overcoming some of its shortcomings. The new system will be a single page reactive web application with shiny web UI containing forecasting model, ARIMA developed with R for the variables of Metocean data stored in Hadoop and spark is integrated to make the computations happen in-memory. The objective is to solve the problem of low speed of matlab and inefficiency of the previous RDBMS. Here, R is replacing functionality of matlab as the backend and Hadoop is replacing the RDBMS as the storage function but distributed file system.. The prediction from arima will be compared to an ML algorithm, Linear Regression, H2O AutoML and the actual data to see its correctness. IRC 2019-09 Final Year Project NonPeerReviewed application/pdf en http://utpedia.utp.edu.my/20962/1/SUMAYEMA%20KABIR%20RICKY_24802.pdf Sumayema, Kabir Ricky (2019) Metocean Prediction using Hadoop, Spark & R. IRC, Universiti Teknologi PETRONAS. (Submitted) |
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Q Science (General) Sumayema, Kabir Ricky Metocean Prediction using Hadoop, Spark & R |
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This project is the development of an analysis system for historical Metocean Data. it is also partial recreation of a previous system overcoming some of its shortcomings. The new system will be a single page reactive web application with shiny web UI containing forecasting model, ARIMA developed with R for the variables of Metocean data stored in Hadoop and spark is integrated to make the computations happen in-memory. The objective is to solve the problem of low speed of matlab and inefficiency of the previous RDBMS. Here, R is replacing functionality of matlab as the backend and Hadoop is replacing the RDBMS as the storage function but distributed file system.. The prediction from arima will be compared to an ML algorithm, Linear Regression, H2O AutoML and the actual data to see its correctness. |
format |
Final Year Project |
author |
Sumayema, Kabir Ricky |
author_facet |
Sumayema, Kabir Ricky |
author_sort |
Sumayema, Kabir Ricky |
title |
Metocean Prediction using Hadoop, Spark & R |
title_short |
Metocean Prediction using Hadoop, Spark & R |
title_full |
Metocean Prediction using Hadoop, Spark & R |
title_fullStr |
Metocean Prediction using Hadoop, Spark & R |
title_full_unstemmed |
Metocean Prediction using Hadoop, Spark & R |
title_sort |
metocean prediction using hadoop, spark & r |
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IRC |
publishDate |
2019 |
url |
http://utpedia.utp.edu.my/20962/1/SUMAYEMA%20KABIR%20RICKY_24802.pdf http://utpedia.utp.edu.my/20962/ |
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13.160551 |