2023
DOI: 10.1016/j.jobe.2023.106589
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PSO-Stacking improved ensemble model for campus building energy consumption forecasting based on priority feature selection

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Cited by 13 publications
(6 citation statements)
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“…This process is essential for enhancing model performance by reducing the dimensionality of the data and eliminating irrelevant or redundant features. Therefore, PSO has been used as an effective technique in many fields, including feature selection [18]. The grey wolf optimizer (GWO) is one of the most recent and popular swarm intelligence algorithms.…”
Section: Imentioning
confidence: 99%
“…This process is essential for enhancing model performance by reducing the dimensionality of the data and eliminating irrelevant or redundant features. Therefore, PSO has been used as an effective technique in many fields, including feature selection [18]. The grey wolf optimizer (GWO) is one of the most recent and popular swarm intelligence algorithms.…”
Section: Imentioning
confidence: 99%
“…HEMSs are often considered as multi-objective optimization arrangements, since they have several features intended to solve multiple problems in order to improve energy efficiency including cost minimization, user comfort, etc. Several algorithms can be used to solve these problems, such as the commonly used genetic algorithms developed by Yang et al or the particle swarm optimization algorithms proposed by Cao et al (Shanghai University of Electric Power) [22,23]. Other less explored alternatives in the current literature include the cuckoo search algorithm and strawberry algorithm studied by Aslam et al and the ant colony algorithm analyzed by Güven et al [24,25].…”
Section: Literature Reviewmentioning
confidence: 99%
“…These particles store their best position as well as the global position. It is this combination of local and global information that gives rise to 'swarm intelligence' [14]. In our study we implemented XGBoost and linear regression algorithms to select the best features.…”
Section: Particle Swarm Optimization (Pso) Algorithmmentioning
confidence: 99%