Artificial Neural Network and Monte Carlo Simulation in a Hybrid Method for Time Series Forecasting with Generation of L-Scenarios

Sometimes, there are time series segment, it is necessary to reconstruct information from the past, predict information for the future, in this paper a hybrid approach between Artificial Neural Network (ANN), Monte Carlo simulation (MCS) for the reconstruction (and / or prediction) of time series wi...

Descripción completa

Guardado en:
Detalles Bibliográficos
Autor Principal: Bermeo Moyano, Henry Vinicio
Formato: Artículos
Publicado: INSTITUTE OF ELECTRICAL AND ELECTRONICS ENGINEERS INC. 2018
Materias:
Acceso en línea:https://www.scopus.com/inward/record.uri?eid=2-s2.0-85013168655&doi=10.1109%2fUIC-ATC-ScalCom-CBDCom-IoP-SmartWorld.2016.0110&partnerID=40&md5=0356ddc13d9825c649b7c6c007a2f706
http://dspace.ucuenca.edu.ec/handle/123456789/29235
Etiquetas: Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
id oai:localhost:123456789-29235
recordtype dspace
spelling oai:localhost:123456789-292352018-02-17T11:26:50Z Artificial Neural Network and Monte Carlo Simulation in a Hybrid Method for Time Series Forecasting with Generation of L-Scenarios Bermeo Moyano, Henry Vinicio ANOVA ARMAX Autocorrelation Chi-square test Monte Carlo Simulation Neural Network Sometimes, there are time series segment, it is necessary to reconstruct information from the past, predict information for the future, in this paper a hybrid approach between Artificial Neural Network (ANN), Monte Carlo simulation (MCS) for the reconstruction (and / or prediction) of time series with the generation of L-scenarios is proposed, in order to evaluate results from hybrid method, the Chi-square test, analysis of variance (ANOVA), functions of autocorrelation were used, additionally, the forecasting ANN is compared with ARMAX model prediction, results show that the proposed method could reconstruct the past, could predict the future from known time series segment, so that each prediction in a whole period selected generates a scenario, the L-scenarios have high sameness statistical from original information. In the hybrid method, first, artificial neural network is trained with known information, second the statistics for the MCS are estimated, then L-scenarios were generated by MCS in the selected period, these information will serve such as inputs for ANN trained, finally these outputs ANN will be the whole time series within in the chosen period, which it want to be analysed. Toulose 2018-01-11T16:47:48Z 2018-01-11T16:47:48Z 2016-07-18 info:eu-repo/semantics/Article 9781509027705 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85013168655&doi=10.1109%2fUIC-ATC-ScalCom-CBDCom-IoP-SmartWorld.2016.0110&partnerID=40&md5=0356ddc13d9825c649b7c6c007a2f706 http://dspace.ucuenca.edu.ec/handle/123456789/29235 10.1109/UIC-ATC-ScalCom-CBDCom-IoP-SmartWorld.2016.0110 en_US instname:Universidad de Cuenca reponame:Repositorio Digital de la Universidad de Cuenca info:eu-repo/semantics/openAccess http://creativecommons.org/licenses/by-nc-sa/3.0/ec/ INSTITUTE OF ELECTRICAL AND ELECTRONICS ENGINEERS INC. Proceedings - 13th IEEE International Conference on Ubiquitous Intelligence and Computing, 13th IEEE International Conference on Advanced and Trusted Computing, 16th IEEE International Conference on Scalable Computing and Communications, IEEE International Conference on Cloud and Big Data Computing, IEEE International Conference on Internet of People and IEEE Smart World Congress and Workshops, UIC-ATC-ScalCom-CBDCom-IoP-SmartWorld 2016 info:eu-repo/date/embargoEnd/2022-01-01 0:00
institution UCUENCA
collection Repositorio UCUENCA
universidades UCUENCA
language
format Artículos
topic ANOVA
ARMAX
Autocorrelation
Chi-square test
Monte Carlo Simulation
Neural Network
spellingShingle ANOVA
ARMAX
Autocorrelation
Chi-square test
Monte Carlo Simulation
Neural Network
Bermeo Moyano, Henry Vinicio
Artificial Neural Network and Monte Carlo Simulation in a Hybrid Method for Time Series Forecasting with Generation of L-Scenarios
description Sometimes, there are time series segment, it is necessary to reconstruct information from the past, predict information for the future, in this paper a hybrid approach between Artificial Neural Network (ANN), Monte Carlo simulation (MCS) for the reconstruction (and / or prediction) of time series with the generation of L-scenarios is proposed, in order to evaluate results from hybrid method, the Chi-square test, analysis of variance (ANOVA), functions of autocorrelation were used, additionally, the forecasting ANN is compared with ARMAX model prediction, results show that the proposed method could reconstruct the past, could predict the future from known time series segment, so that each prediction in a whole period selected generates a scenario, the L-scenarios have high sameness statistical from original information. In the hybrid method, first, artificial neural network is trained with known information, second the statistics for the MCS are estimated, then L-scenarios were generated by MCS in the selected period, these information will serve such as inputs for ANN trained, finally these outputs ANN will be the whole time series within in the chosen period, which it want to be analysed.
author Bermeo Moyano, Henry Vinicio
author_facet Bermeo Moyano, Henry Vinicio
author_sort Bermeo Moyano, Henry Vinicio
title Artificial Neural Network and Monte Carlo Simulation in a Hybrid Method for Time Series Forecasting with Generation of L-Scenarios
title_short Artificial Neural Network and Monte Carlo Simulation in a Hybrid Method for Time Series Forecasting with Generation of L-Scenarios
title_full Artificial Neural Network and Monte Carlo Simulation in a Hybrid Method for Time Series Forecasting with Generation of L-Scenarios
title_fullStr Artificial Neural Network and Monte Carlo Simulation in a Hybrid Method for Time Series Forecasting with Generation of L-Scenarios
title_full_unstemmed Artificial Neural Network and Monte Carlo Simulation in a Hybrid Method for Time Series Forecasting with Generation of L-Scenarios
title_sort artificial neural network and monte carlo simulation in a hybrid method for time series forecasting with generation of l-scenarios
publisher INSTITUTE OF ELECTRICAL AND ELECTRONICS ENGINEERS INC.
publishDate 2018
url https://www.scopus.com/inward/record.uri?eid=2-s2.0-85013168655&doi=10.1109%2fUIC-ATC-ScalCom-CBDCom-IoP-SmartWorld.2016.0110&partnerID=40&md5=0356ddc13d9825c649b7c6c007a2f706
http://dspace.ucuenca.edu.ec/handle/123456789/29235
_version_ 1635523465723248640
score 11,871979