Lorenz time-series analysis using a scaled hybrid model

Lorenz time-series is characterized by non-linearity, noise, volatility and is chaotic in nature thus making the process of forecasting cumbersome. The main aim of forecasters is to apply an approach that focuses on improving accuracy in both one-step and multi-step-ahead forecasts. This paper prese...

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Main Authors: Abdulkadir, S.J., Yong, S.-P.
Format: Conference or Workshop Item
Institution: Universiti Teknologi Petronas
Record Id / ISBN-0: utp-eprints.30911 /
Published: Institute of Electrical and Electronics Engineers Inc. 2016
Online Access: https://www.scopus.com/inward/record.uri?eid=2-s2.0-84995616526&doi=10.1109%2fISMSC.2015.7594082&partnerID=40&md5=7668b2df1c11192aaaefbcf4c16d9c33
http://eprints.utp.edu.my/30911/
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spelling utp-eprints.309112022-03-25T07:43:24Z Lorenz time-series analysis using a scaled hybrid model Abdulkadir, S.J. Yong, S.-P. Lorenz time-series is characterized by non-linearity, noise, volatility and is chaotic in nature thus making the process of forecasting cumbersome. The main aim of forecasters is to apply an approach that focuses on improving accuracy in both one-step and multi-step-ahead forecasts. This paper presents an empirical analysis of Lorenz time-series using Scaled UKF-NARX hybrid model to perform one-step and multi-step-ahead forecasts. The proposed hybrid model is trained using Bayesian regulation algorithm. The experimental results based on two forecatingg erorr metrics, normalized mean squared error (NMSE) and root mean square error (RMSE) shows that proposed hybrid model provides better multi-step-ahead forecasts whilst addressing the issue of long term dependencies. © 2015 IEEE. Institute of Electrical and Electronics Engineers Inc. 2016 Conference or Workshop Item NonPeerReviewed https://www.scopus.com/inward/record.uri?eid=2-s2.0-84995616526&doi=10.1109%2fISMSC.2015.7594082&partnerID=40&md5=7668b2df1c11192aaaefbcf4c16d9c33 Abdulkadir, S.J. and Yong, S.-P. (2016) Lorenz time-series analysis using a scaled hybrid model. In: UNSPECIFIED. http://eprints.utp.edu.my/30911/
institution Universiti Teknologi Petronas
collection UTP Institutional Repository
description Lorenz time-series is characterized by non-linearity, noise, volatility and is chaotic in nature thus making the process of forecasting cumbersome. The main aim of forecasters is to apply an approach that focuses on improving accuracy in both one-step and multi-step-ahead forecasts. This paper presents an empirical analysis of Lorenz time-series using Scaled UKF-NARX hybrid model to perform one-step and multi-step-ahead forecasts. The proposed hybrid model is trained using Bayesian regulation algorithm. The experimental results based on two forecatingg erorr metrics, normalized mean squared error (NMSE) and root mean square error (RMSE) shows that proposed hybrid model provides better multi-step-ahead forecasts whilst addressing the issue of long term dependencies. © 2015 IEEE.
format Conference or Workshop Item
author Abdulkadir, S.J.
Yong, S.-P.
spellingShingle Abdulkadir, S.J.
Yong, S.-P.
Lorenz time-series analysis using a scaled hybrid model
author_sort Abdulkadir, S.J.
title Lorenz time-series analysis using a scaled hybrid model
title_short Lorenz time-series analysis using a scaled hybrid model
title_full Lorenz time-series analysis using a scaled hybrid model
title_fullStr Lorenz time-series analysis using a scaled hybrid model
title_full_unstemmed Lorenz time-series analysis using a scaled hybrid model
title_sort lorenz time-series analysis using a scaled hybrid model
publisher Institute of Electrical and Electronics Engineers Inc.
publishDate 2016
url https://www.scopus.com/inward/record.uri?eid=2-s2.0-84995616526&doi=10.1109%2fISMSC.2015.7594082&partnerID=40&md5=7668b2df1c11192aaaefbcf4c16d9c33
http://eprints.utp.edu.my/30911/
_version_ 1741197488269819904
score 11.62408

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