Forecasting of monthly temperature variations using random forests

This study utilized a random forest model for monthly temperature forecasting of KL by using historical time series data of (2000 to 2012). Random Forest is an ensemble learning method that generates many regression trees (CART) and aggregates their results. The model operates on patterns of the tim...

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Main Authors:	Nyein Naing, Wai Yan, Htike@Muhammad Yusof, Zaw Zaw
Format:	Conference or Workshop Item
Language:	English
Published:	2015
Subjects:	T Technology (General)
Online Access:	http://irep.iium.edu.my/47995/ http://irep.iium.edu.my/47995/ http://irep.iium.edu.my/47995/1/125.pdf

id	iium-47995
recordtype	eprints
spelling	iium-479952018-06-26T02:58:37Z http://irep.iium.edu.my/47995/ Forecasting of monthly temperature variations using random forests Nyein Naing, Wai Yan Htike@Muhammad Yusof, Zaw Zaw T Technology (General) This study utilized a random forest model for monthly temperature forecasting of KL by using historical time series data of (2000 to 2012). Random Forest is an ensemble learning method that generates many regression trees (CART) and aggregates their results. The model operates on patterns of the time series seasonal cycles which simplifies the forecasting problem especially when a time series exhibits nonstationarity, heteroscedasticity, trend and multiple seasonal cycles. The main advantages of the model are its ability to generalization, built-in cross-validation and low sensitivity to parameter values. As an illustration, the proposed forecasting model is applied to historical load data in Kuala Lumpur (2000 to 2012) and its performance is compared with some alternative models such as K-Nearest Neighbours , Least Medium square Regression , RBF (Radial Basic Function) network and MLP (Multilayer Perceptron) neural networks. Application examples confirm good properties of the model and its high accuracy. 2015 Conference or Workshop Item PeerReviewed application/pdf en http://irep.iium.edu.my/47995/1/125.pdf Nyein Naing, Wai Yan and Htike@Muhammad Yusof, Zaw Zaw (2015) Forecasting of monthly temperature variations using random forests. In: International Postgraduate Conference on Engineering Research (IPCER) 2015 , 27th-28th Oct. 2015, Gombak Campus, IIUM. (In Press) http://www.iium.edu.my/ipcer/15/
repository_type	Digital Repository
institution_category	Local University
institution	International Islamic University Malaysia
building	IIUM Repository
collection	Online Access
language	English
topic	T Technology (General)
spellingShingle	T Technology (General) Nyein Naing, Wai Yan Htike@Muhammad Yusof, Zaw Zaw Forecasting of monthly temperature variations using random forests
description	This study utilized a random forest model for monthly temperature forecasting of KL by using historical time series data of (2000 to 2012). Random Forest is an ensemble learning method that generates many regression trees (CART) and aggregates their results. The model operates on patterns of the time series seasonal cycles which simplifies the forecasting problem especially when a time series exhibits nonstationarity, heteroscedasticity, trend and multiple seasonal cycles. The main advantages of the model are its ability to generalization, built-in cross-validation and low sensitivity to parameter values. As an illustration, the proposed forecasting model is applied to historical load data in Kuala Lumpur (2000 to 2012) and its performance is compared with some alternative models such as K-Nearest Neighbours , Least Medium square Regression , RBF (Radial Basic Function) network and MLP (Multilayer Perceptron) neural networks. Application examples confirm good properties of the model and its high accuracy.
format	Conference or Workshop Item
author	Nyein Naing, Wai Yan Htike@Muhammad Yusof, Zaw Zaw
author_facet	Nyein Naing, Wai Yan Htike@Muhammad Yusof, Zaw Zaw
author_sort	Nyein Naing, Wai Yan
title	Forecasting of monthly temperature variations using random forests
title_short	Forecasting of monthly temperature variations using random forests
title_full	Forecasting of monthly temperature variations using random forests
title_fullStr	Forecasting of monthly temperature variations using random forests
title_full_unstemmed	Forecasting of monthly temperature variations using random forests
title_sort	forecasting of monthly temperature variations using random forests
publishDate	2015
url	http://irep.iium.edu.my/47995/ http://irep.iium.edu.my/47995/ http://irep.iium.edu.my/47995/1/125.pdf
first_indexed	2023-09-18T21:08:12Z
last_indexed	2023-09-18T21:08:12Z
_version_	1777411075931635712

Forecasting of monthly temperature variations using random forests

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