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Hossein Moayedi, Dieu Tien Bui and Phuong Thao Thi Ngo
The prediction aptitude of an artificial neural network (ANN) is improved by incorporating two novel metaheuristic techniques, namely, the shuffled frog leaping algorithm (SFLA) and wind-driven optimization (WDO), for the purpose of soil shear strength (...
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Hossein Moayedi, Dieu Tien Bui, Anastasios Dounis, Loke Kok Foong and Bahareh Kalantar
This paper focuses on the prediction of soil shear strength (SSS), which is one of the most fundamental parameters in geotechnical engineering. Consisting of 12 influential factors, namely depth of sample, percentage of sand, percentage of loam, percenta...
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Hossein Moayedi, Dieu Tien Bui, Bahareh Kalantar and Loke Kok Foong
In this paper, the authors investigated the applicability of combining machine-learning-based models toward slope stability assessment. To do this, several well-known machine-learning-based methods, namely multiple linear regression (MLR), multi-layer pe...
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Hossein Moayedi, Bahareh Kalantar, Loke Kok Foong, Dieu Tien Bui and Alireza Motevalli
Slump is a workability-related characteristic of concrete mixture. This paper investigates the efficiency of a novel optimizer, namely ant lion optimization (ALO), for fine-tuning of a neural network (NN) in the field of concrete slump prediction. Two we...
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Hossein Moayedi, Dieu Tien Bui, Anastasios Dounis, Zongjie Lyu and Loke Kok Foong
The heating load calculation is the first step of the iterative heating, ventilation, and air conditioning (HVAC) design procedure. In this study, we employed six machine learning techniques, namely multi-layer perceptron regressor (MLPr), lazy locally w...
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Le Thi Le, Hoang Nguyen, Jian Zhou, Jie Dou and Hossein Moayedi
In this study, a novel technique to support smart city planning in estimating and controlling the heating load (HL) of buildings, was proposed, namely PSO-XGBoost. Accordingly, the extreme gradient boosting machine (XGBoost) was developed to estimate HL ...
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Dieu Tien Bui, Hossein Moayedi, Mesut Gör, Abolfazl Jaafari and Loke Kok Foong
In this study, we employed various machine learning-based techniques in predicting factor of safety against slope failures. Different regression methods namely, multi-layer perceptron (MLP), Gaussian process regression (GPR), multiple linear regression (...
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Hossein Moayedi, Dieu Tien Bui, Mesut Gör, Biswajeet Pradhan and Abolfazl Jaafari
In this paper, a neuro particle-based optimization of the artificial neural network (ANN) is investigated for slope stability calculation. The results are also compared to another artificial intelligence technique of a conventional ANN and adaptive neuro...
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