A Comparative Study of PSO-ANN, GA-ANN, ICA-ANN, and ABC-ANN in Estimating the Heating Load of Buildings’ Energy Efficiency for Smart City Planning
By L. Le, Hoang Nguyen, Jie Dou, Jian Zhou. Applied Sciences, 2019
298 citations recorded by the source corpus.
Energy-efficiency is one of the critical issues in smart cities. It is an essential basis for optimizing smart cities planning. This study proposed four new artificial intelligence (AI) techniques for forecasting the heating load of buildings’ energy efficiency based on the potential of artificial neural network (ANN) and meta-heuristics algorithms, including artificial bee colony (ABC) optimization, particle swarm optimization (PSO), imperialist competitive algorithm (ICA), and genetic algorithm (GA). They were abbreviated as ABC-ANN, PSO-ANN, ICA-ANN, and GA-ANN models; 837 buildings were considered and analyzed based on the influential parameters, such as glazing area distribution (GLAD), glazing area (GLA), orientation (O), overall height (OH), roof area (RA), wall area (WA), surface area (SA), relative compactness (RC), for estimating heating load (HL). Three statistical criteria, such as root-mean-squared error (RMSE), coefficient determination (R2), and mean absolute error (MAE), were used to assess the potential of the aforementioned models. The results indicated that the GA-ANN model provided the highest performance in estimating the heating load of buildings’ energy efficiency, with an RMSE of 1.625, R2 of 0.980, and MAE of 0.798. The remaining models (i.e., PSO-ANN, ICA-ANN, ABC-ANN) yielded lower performance with RMSE of 1.932, 1.982, 1.878; R2 of 0.972, 0.970, 0.973; MAE of 1.027, 0.980, 0.957, respectively.
Subfields: Building and Construction, Electrical and Electronic Engineering, Environmental Engineering
View Paper: https://www.semanticscholar.org/paper/c36645bec2c17de33a38f30813982e65c02eb909
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Citations in the corpus
- A novel artificial intelligence technique to predict compressive strength of recycled aggregate concrete using ICA-XGBoost model (2020, background): “Actually, ICA is a global search algorithm that is developed based on imperialist competition and social policies [64].”