Influence of data splitting on performance of machine learning models in prediction of shear strength of soil

QH Nguyen, HB Ly, LS Ho, N Al-Ansari… - Mathematical …, 2021 - Wiley Online Library
The main objective of this study is to evaluate and compare the performance of different
machine learning (ML) algorithms, namely, Artificial Neural Network (ANN), Extreme …

[HTML][HTML] Robust machine learning algorithms for predicting coastal water quality index

MG Uddin, S Nash, MTM Diganta, A Rahman… - Journal of …, 2022 - Elsevier
Coastal water quality assessment is an essential task to keep “good water quality” status for
living organisms in coastal ecosystems. The Water quality index (WQI) is a widely used tool …

[HTML][HTML] Evaluation of deep learning algorithms for national scale landslide susceptibility mapping of Iran

PTT Ngo, M Panahi, K Khosravi, O Ghorbanzadeh… - Geoscience …, 2021 - Elsevier
The identification of landslide-prone areas is an essential step in landslide hazard
assessment and mitigation of landslide-related losses. In this study, we applied two novel …

Convolutional neural network (CNN) with metaheuristic optimization algorithms for landslide susceptibility mapping in Icheon, South Korea

WL Hakim, F Rezaie, AS Nur, M Panahi… - Journal of environmental …, 2022 - Elsevier
Landslides are a geological hazard that can pose a serious threat to human health and the
environment of highlands or mountain slopes. Landslide susceptibility mapping is an …

A comparative assessment of flood susceptibility modeling using multi-criteria decision-making analysis and machine learning methods

K Khosravi, H Shahabi, BT Pham, J Adamowski… - Journal of …, 2019 - Elsevier
Floods around the world are having devastating effects on human life and property. In this
paper, three Multi-Criteria Decision-Making (MCDM) analysis techniques (VIKOR, TOPSIS …

Improving prediction of water quality indices using novel hybrid machine-learning algorithms

DT Bui, K Khosravi, J Tiefenbacher, H Nguyen… - Science of the Total …, 2020 - Elsevier
River water quality assessment is one of the most important tasks to enhance water
resources management plans. A water quality index (WQI) considers several water quality …

Assessment of landslide susceptibility along mountain highways based on different machine learning algorithms and mapping units by hybrid factors screening and …

D Sun, Q Gu, H Wen, J Xu, Y Zhang, S Shi, M Xue… - Gondwana …, 2023 - Elsevier
To develop a better spatial prediction model of landslide susceptibility along mountain
highways, this study compared assessment models of landslide susceptibility along …

[HTML][HTML] Landslide susceptibility modeling based on ANFIS with teaching-learning-based optimization and Satin bowerbird optimizer

W Chen, X Chen, J Peng, M Panahi, S Lee - Geoscience Frontiers, 2021 - Elsevier
As threats of landslide hazards have become gradually more severe in recent decades,
studies on landslide prevention and mitigation have attracted widespread attention in …

Comparative study of landslide susceptibility mapping with different recurrent neural networks

Y Wang, Z Fang, M Wang, L Peng, H Hong - Computers & Geosciences, 2020 - Elsevier
This paper aims to use recurrent neural networks (RNNs) to perform landslide susceptibility
mapping in Yongxin County, China. The two main contributions of this study are summarized …

[HTML][HTML] Soft computing ensemble models based on logistic regression for groundwater potential mapping

PT Nguyen, DH Ha, M Avand, A Jaafari, HD Nguyen… - Applied Sciences, 2020 - mdpi.com
Groundwater potential maps are one of the most important tools for the management of
groundwater storage resources. In this study, we proposed four ensemble soft computing …