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Engineering with Computers
Erschienen in: Engineering with Computers 3/2020

01.04.2019 | Original Article

Proposing a novel predictive technique using M5Rules-PSO model estimating cooling load in energy-efficient building system

verfasst von: Hoang Nguyen, Hossein Moayedi, Wan Amizah Wan Jusoh, Abolhasan Sharifi

Erschienen in: Engineering with Computers | Ausgabe 3/2020

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Abstract

In this study, we employed the most suitable artificial intelligence systems and optimized it with a novel evolutionary algorithm called particle swarm optimization (PSO) for the problem of cooling load (CL) in energy-efficient building (EEB) system. Then, the mentioned methods are utilised to identify a relationship between the input and output parameters of the EEB system. The amount of CL was taken as the essential output of the EEB system, while the input parameters were channel length, channel depth, channel width, and air mass flow rate. The predicted results for data sets from each of the abovementioned models were evaluated according to several known statistical indices such as correlation coefficient (R2), mean absolute error (MAE), root mean squared error (RMSE), relative absolute error (RAE), and root relative squared error (RRSE) as well as novel ranking systems of colour intensity rating and total ranking method. The M5Rules has been proposed as the best predictive network in this study. The results of the M5Rules network indicated the R2, MAE, RMSE, RAE, and RRSE for the training and testing data sets were 0.9982, 0.0426, 0.0653, 6.2344, and 6.0298 and 0.7626, 0.9903, 0.9593, and 0.9981, respectively. According to R2, RMSE, and VAF, values of 0.99983, 0.0066, and 99.98 and 0.9982, 0.065, and 84.5 were obtained for testing data set and values of proposed PSO-M5Rules prediction network models, respectively. This indicates higher reliability of the introduced PSO-M5Rules model in approximating CL of an EEB system.
Vorheriger Artikel An efficient wavelet collocation method for nonlinear two-space dimensional Fisher–Kolmogorov–Petrovsky–Piscounov equation and two-space dimensional extended Fisher–Kolmogorov equation
Nächster Artikel Numerical approach for solving variable-order space–time fractional telegraph equation using transcendental Bernstein series

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Metadaten
Titel
Proposing a novel predictive technique using M5Rules-PSO model estimating cooling load in energy-efficient building system
verfasst von
Hoang Nguyen
Hossein Moayedi
Wan Amizah Wan Jusoh
Abolhasan Sharifi
Publikationsdatum
01.04.2019
Verlag
Springer London
Erschienen in
Engineering with Computers / Ausgabe 3/2020
Print ISSN: 0177-0667
Elektronische ISSN: 1435-5663
DOI
https://doi.org/10.1007/s00366-019-00735-y

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