Machine learning in environmental research: common pitfalls and best practices

JJ Zhu, M Yang, ZJ Ren - Environmental Science & Technology, 2023 - ACS Publications
Machine learning (ML) is increasingly used in environmental research to process large data
sets and decipher complex relationships between system variables. However, due to the …

Applications of artificial intelligence for disaster management

W Sun, P Bocchini, BD Davison - Natural Hazards, 2020 - Springer
Natural hazards have the potential to cause catastrophic damage and significant
socioeconomic loss. The actual damage and loss observed in the recent decades has …

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 …

Comparisons of heuristic, general statistical and machine learning models for landslide susceptibility prediction and map**

F Huang, Z Cao, J Guo, SH Jiang, S Li, Z Guo - Catena, 2020 - Elsevier
Commonly used data-driven models for landslide susceptibility prediction (LSP) can be
mainly classified as heuristic, general statistical or machine learning models. This study …

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 …

Machine learning based wildfire susceptibility map** using remotely sensed fire data and GIS: A case study of Adana and Mersin provinces, Turkey

MC Iban, A Sekertekin - Ecological Informatics, 2022 - Elsevier
In recent years, the number of wildfires has increased all over the world. Therefore, map**
wildfire susceptibility is crucial for prevention, early detection, and supporting wildfire …

[HTML][HTML] Uncertainties of landslide susceptibility prediction considering different landslide types

F Huang, H **: A comparison between logistic model tree, logistic regression, naïve bayes tree, artificial neural network, and support vector …
VH Nhu, A Shirzadi, H Shahabi, SK Singh… - International journal of …, 2020 - mdpi.com
Shallow landslides damage buildings and other infrastructure, disrupt agriculture practices,
and can cause social upheaval and loss of life. As a result, many scientists study the …