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A novel evolutionary approach to linear time-series forecasting model

cris.author.scopus-author-id57214585344
cris.author.scopus-author-id57195773359
dc.contributor.authorVijayan, Prakash
dc.contributor.authorSuresh, S.
dc.date.accessioned2023-09-20T05:35:41Z
dc.date.available2023-09-20T05:35:41Z
dc.date.issued01-01-2003
dc.description.abstractThis paper presents a handshake between the concepts of genetic algorithms and the forecasting problem to present a novel search based multiphase genetic algorithm to the forecasting problem based on the time series model. The backbone concept of the paper lies in utilizing the genetic approach effectively for implementing the Autoregressive process, a linear stochastic model where a time series is supposed to be a linear aggregation of random shocks. We propose to utilize the concept of genetic algorithms to transform an initial population of random suggested solutions to a population that contains solutions approximating the optimal one. A carefully chosen fitness function acts in the capacity of a yardstick to appraise the quality of each "chromosome" to aid the selection phase. We simulated the presented approach on a Pentium IV processor and obtained results that were very encouraging. © Springer-Verlag Berlin Heidelberg 2003.
dc.identifier.doi10.1007/3-540-44864-0_93
dc.identifier.issn3029743
dc.identifier.scopus2-s2.0-35248869265
dc.identifier.urihttps://apicris.irins.org/handle/IITM2023/49645
dc.relation.ispartofseriesLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
dc.sourceLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
dc.titleA novel evolutionary approach to linear time-series forecasting model
dc.typeBook Series
dspace.entity.typePublication
oaire.citation.endPage910
oaire.citation.startPage903
oaire.citation.volume2660
person.affiliation.cityChennai
person.affiliation.id60025757
person.affiliation.nameIndian Institute of Technology Madras
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