Energy Consumption Forecasting Using Semantic-Based Genetic Programming with Local Search Optimizer

Bibliographic Details
Main Author: Castelli, Mauro
Publication Date: 2015
Other Authors: Trujillo, Leonardo, Vanneschi, Leonardo
Format: Article
Language: eng
Source: Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
Download full: https://doi.org/10.1155/2015/971908
Summary: Castelli, M., Trujillo, L., & Vanneschi, L. (2015). Energy Consumption Forecasting Using Semantic-Based Genetic Programming with Local Search Optimizer. Computational Intelligence And Neuroscience, 2015, [971908]. https://doi.org/10.1155/2015/971908
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spelling Energy Consumption Forecasting Using Semantic-Based Genetic Programming with Local Search OptimizerNeuroscience(all)Computer Science(all)Mathematics(all)SDG 7 - Affordable and Clean EnergyCastelli, M., Trujillo, L., & Vanneschi, L. (2015). Energy Consumption Forecasting Using Semantic-Based Genetic Programming with Local Search Optimizer. Computational Intelligence And Neuroscience, 2015, [971908]. https://doi.org/10.1155/2015/971908Energy consumption forecasting (ECF) is an important policy issue in today's economies. An accurate ECF has great benefits for electric utilities and both negative and positive errors lead to increased operating costs. The paper proposes a semantic based genetic programming framework to address the ECF problem. In particular, we propose a system that finds (quasi-)perfect solutions with high probability and that generates models able to produce near optimal predictions also on unseen data. The framework blends a recently developed version of genetic programming that integrates semantic genetic operators with a local search method. The main idea in combining semantic genetic programming and a local searcher is to couple the exploration ability of the former with the exploitation ability of the latter. Experimental results confirm the suitability of the proposed method in predicting the energy consumption. In particular, the system produces a lower error with respect to the existing state-of-the art techniques used on the same dataset. More importantly, this case study has shown that including a local searcher in the geometric semantic genetic programming system can speed up the search process and can result in fitter models that are able to produce an accurate forecasting also on unseen data.NOVA Information Management School (NOVA IMS)Information Management Research Center (MagIC) - NOVA Information Management SchoolRUNCastelli, MauroTrujillo, LeonardoVanneschi, Leonardo2019-05-29T22:08:14Z2015-01-012015-01-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/article8application/pdfhttps://doi.org/10.1155/2015/971908eng1687-5265PURE: 13514750http://www.scopus.com/inward/record.url?scp=84935915289&partnerID=8YFLogxKhttps://doi.org/10.1155/2015/971908info:eu-repo/semantics/openAccessreponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiainstacron:RCAAP2024-05-22T17:39:49Zoai:run.unl.pt:10362/71193Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireinfo@rcaap.ptopendoar:https://opendoar.ac.uk/repository/71602025-05-28T17:10:57.117161Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiafalse
dc.title.none.fl_str_mv Energy Consumption Forecasting Using Semantic-Based Genetic Programming with Local Search Optimizer
title Energy Consumption Forecasting Using Semantic-Based Genetic Programming with Local Search Optimizer
spellingShingle Energy Consumption Forecasting Using Semantic-Based Genetic Programming with Local Search Optimizer
Castelli, Mauro
Neuroscience(all)
Computer Science(all)
Mathematics(all)
SDG 7 - Affordable and Clean Energy
title_short Energy Consumption Forecasting Using Semantic-Based Genetic Programming with Local Search Optimizer
title_full Energy Consumption Forecasting Using Semantic-Based Genetic Programming with Local Search Optimizer
title_fullStr Energy Consumption Forecasting Using Semantic-Based Genetic Programming with Local Search Optimizer
title_full_unstemmed Energy Consumption Forecasting Using Semantic-Based Genetic Programming with Local Search Optimizer
title_sort Energy Consumption Forecasting Using Semantic-Based Genetic Programming with Local Search Optimizer
author Castelli, Mauro
author_facet Castelli, Mauro
Trujillo, Leonardo
Vanneschi, Leonardo
author_role author
author2 Trujillo, Leonardo
Vanneschi, Leonardo
author2_role author
author
dc.contributor.none.fl_str_mv NOVA Information Management School (NOVA IMS)
Information Management Research Center (MagIC) - NOVA Information Management School
RUN
dc.contributor.author.fl_str_mv Castelli, Mauro
Trujillo, Leonardo
Vanneschi, Leonardo
dc.subject.por.fl_str_mv Neuroscience(all)
Computer Science(all)
Mathematics(all)
SDG 7 - Affordable and Clean Energy
topic Neuroscience(all)
Computer Science(all)
Mathematics(all)
SDG 7 - Affordable and Clean Energy
description Castelli, M., Trujillo, L., & Vanneschi, L. (2015). Energy Consumption Forecasting Using Semantic-Based Genetic Programming with Local Search Optimizer. Computational Intelligence And Neuroscience, 2015, [971908]. https://doi.org/10.1155/2015/971908
publishDate 2015
dc.date.none.fl_str_mv 2015-01-01
2015-01-01T00:00:00Z
2019-05-29T22:08:14Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv https://doi.org/10.1155/2015/971908
url https://doi.org/10.1155/2015/971908
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 1687-5265
PURE: 13514750
http://www.scopus.com/inward/record.url?scp=84935915289&partnerID=8YFLogxK
https://doi.org/10.1155/2015/971908
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv 8
application/pdf
dc.source.none.fl_str_mv reponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia
instacron:RCAAP
instname_str FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia
instacron_str RCAAP
institution RCAAP
reponame_str Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
collection Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
repository.name.fl_str_mv Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia
repository.mail.fl_str_mv info@rcaap.pt
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