A HYBRID LEAST SQUARES SUPPORT VECTOR MACHINE WITH BAT AND CUCKOO SEARCH ALGORITHMS FOR TIME SERIES FORECASTING

A HYBRID LEAST SQUARES SUPPORT VECTOR MACHINE WITH BAT AND CUCKOO SEARCH ALGORITHMS FOR TIME SERIES FORECASTING

Least Squares Support Vector Machine (LSSVM) has been known to be one of the effective forecasting models. However, its operation relies on two important parameters (regularization and kernel). Pre-determining the values of parameters will affect the results of the forecasting model; hence, to find...

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Détails bibliographiques
Auteurs principaux: Athraa Jasim Mohammed, Khalil Ibrahim Ghathwan, Yuhanis Yusof
Format: article
Langue:EN
Publié: UUM Press 2020
Sujets:
machine learning
data mining
time series forecasting
least squares support vector machine
particle swarm optimization
Information technology
T58.5-58.64
Accès en ligne:https://doaj.org/article/1d0782e9d6044450a648da9668b491a9
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https://doaj.org/article/1d0782e9d6044450a648da9668b491a9

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