Browsing Handelshøyskolen by Journals "Applied Sciences"
Now showing items 1-13 of 13
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Application of Three Metaheuristic Techniques in Simulation of Concrete Slump
(Journal article; Peer reviewed, 2019)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 ... -
Development of a Novel Hybrid Intelligence Approach for Landslide Spatial Prediction
(Peer reviewed; Journal article, 2019)We proposed an innovative hybrid intelligent approach, namely, the multiboost based naïve bayes trees (MBNBT) method for the spatial prediction of landslides in the Mu Cang Chai District of Yen Bai Province, Vietnam. The ... -
Development of Two Novel Hybrid Prediction Models Estimating Ultimate Bearing Capacity of the Shallow Circular Footing
(Peer reviewed; Journal article, 2019)In the present work, we employed artificial neural network (ANN) that is optimized with two hybrid models, namely imperialist competition algorithm (ICA) as well as particle swarm optimization (PSO) in the case of the ... -
Enhancing Prediction Performance of Landslide Susceptibility Model Using Hybrid Machine Learning Approach of Bagging Ensemble and Logistic Model Tree
(Journal article; Peer reviewed, 2018)The objective of this research is introduce a new machine learning ensemble approach that is a hybridization of Bagging ensemble (BE) and Logistic Model Trees (LMTree), named as BE-LMtree, for improving performance of ... -
Machine-Learning-Based Classification Approaches toward Recognizing Slope Stability Failure
(Peer reviewed; Journal article, 2019)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 ... -
Neural Computing Improvement Using Four Metaheuristic Optimizers in Bearing Capacity Analysis of Footings Settled on Two-Layer Soils
(Peer reviewed; Journal article, 2019)This study outlines the applicability of four metaheuristic algorithms, namely, whale optimization algorithm (WOA), league champion optimization (LCA), moth–flame optimization (MFO), and ant colony optimization (ACO), for ... -
A New Approach of Hybrid Bee Colony Optimized Neural Computing for Estimation of Soil Compression Coefficient for Housing Construction Project
(Peer reviewed; Journal article, 2019)In the design phase of housing projects, predicting the settlement of soil layers beneath the buildings requires the estimation of the coefficient of soil compression. This study proposes a low-cost, fast, and reliable ... -
A New Integrated Approach Based on the Iterative Super-Resolution Algorithm and Expectation Maximization for Face Hallucination
(Peer reviewed; Journal article, 2020)This paper proposed and verified a new integrated approach based on the iterative super-resolution algorithm and expectation-maximization for face hallucination, which is a process of converting a low-resolution face image ... -
A Novel Application of League Championship Optimization (LCA): Hybridizing Fuzzy Logic for Soil Compression Coefficient Analysis
(Peer reviewed; Journal article, 2020)Employing league championship optimization (LCA) technique for adjusting the membership function parameters of the adaptive neuro-fuzzy inference system (ANFIS) is the focal objective of the present study. The mentioned ... -
Novel Nature-Inspired Hybrids of Neural Computing for Estimating Soil Shear Strength
(Peer reviewed; Journal article, 2019)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 ... -
Predicting Heating Load in Energy-Efficient Buildings Through Machine Learning Techniques
(Peer reviewed; Journal article, 2019)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 ... -
Shuffled Frog Leaping Algorithm and Wind-Driven Optimization Technique Modified with Multilayer Perceptron
(Peer reviewed; Journal article, 2020)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 ... -
Spotted Hyena Optimizer and Ant Lion Optimization in Predicting the Shear Strength of Soil
(Peer reviewed; Journal article, 2019)Two novel hybrid predictors are suggested as the combination of artificial neural network (ANN), coupled with spotted hyena optimizer (SHO) and ant lion optimization (ALO) metaheuristic techniques, to simulate soil shear ...