Machine learning data-driven approaches for land use/cover mapping and trend analysis using Google Earth Engine

B Feizizadeh, D Omarzadeh… - Journal of …, 2023 - Taylor & Francis
With the recent advances in earth observation technologies, the increasing availability of
data from more and more different satellite sensors as well as progress in semi-automated …

[HTML][HTML] Health effects of shrinking hyper-saline lakes: spatiotemporal modeling of the Lake Urmia drought on the local population, case study of the Shabestar County

B Feizizadeh, T Lakes, D Omarzadeh… - Scientific Reports, 2023 - nature.com
Climate change and its respective environmental impacts, such as dying lakes, is widely
acknowledged. Studies on the impact of shrinking hyper-saline lakes suggest severe …

[HTML][HTML] Utilizing hybrid machine learning and soft computing techniques for landslide susceptibility mapping in a Drainage Basin

Y Mao, Y Li, F Teng, AKS Sabonchi, M Azarafza… - Water, 2024 - mdpi.com
The hydrological system of thebasin of Lake Urmia is complex, deriving its supply from a
network comprising 13 perennial rivers, along withnumerous small springs and direct …

Image processing-based automatic detection of asphalt pavement rutting using a novel metaheuristic optimized machine learning approach

MT Cao, KT Chang, NM Nguyen, VD Tran, XL Tran… - Soft Computing, 2021 - Springer
Pavement rutting refers to surface depression in the wheel-path along an asphalt road which
causes loss of steering control and consequently leads to serious traffic accidents. Hence, it …

A comparison study on the quantitative statistical methods for spatial prediction of shallow landslides (case study: Yozidar-Degaga Route in Kurdistan Province, Iran)

M Asadi, L Goli Mokhtari, A Shirzadi, H Shahabi… - Environmental Earth …, 2022 - Springer
The main purpose of this study was to compare the performance of Support Vector Machines
(SVM), Stochastic Gradient Descent (SGD), and Bayesian Logistic Regression (BLR) …

Enhancing slope stability prediction using fuzzy and neural frameworks optimized by metaheuristic science

MA Mu'azu - Mathematical Geosciences, 2023 - Springer
Recently, machine learning models have acted as effective tools for slope stability analysis.
But due to the crucial significance of this issue, reaching a reliable accuracy is necessary …

[HTML][HTML] Risk Factors and Prediction of the Probability of Wildfire Occurrence in the China–Mongolia–Russia Cross-Border Area

Y Li, S Xu, Z Fan, X Zhang, X Yang, S Wen, Z Shi - Remote Sensing, 2022 - mdpi.com
Wildfire is essential in altering land ecosystems' structures, processes, and functions. As a
critical disturbance in the China–Mongolia–Russia cross-border area, it is vital to …

[HTML][HTML] A quasi-affine transformation evolutionary algorithm enhanced by hybrid Taguchi strategy and its application in fault detection of wireless sensor network

JS Pan, RY Wang, SC Chu, KK Tseng, F Fan - Symmetry, 2023 - mdpi.com
A quasi-affine transformation evolutionary algorithm improved by the Taguchi strategy, levy
flight and the restart mechanism (TLR-QUATRE) is proposed in this paper. This algorithm …

Using the integrated application of computational intelligence for landslide susceptibility modeling in East Azerbaijan Province, Iran

S Abdollahizad, MA Balafar, B Feizizadeh… - Applied …, 2023 - Springer
Mapping of landslide susceptibility is an important tool to prevent and control landslide
disasters for a variety of applications, such as land use management plans. The main …

[HTML][HTML] A hybrid variable weight theory approach of hierarchical analysis and multi-layer perceptron for landslide susceptibility evaluation: a case study in Luanchuan …

M Li, Y Guo, D Luo, C Ma - Sustainability, 2023 - mdpi.com
Landslides, which can cause significant losses of lives or property damages, result from
several different environmental factors whose influences are very complex. Thus, the …