Machine learning based landslide susceptibility mapping models and GB-SAR based landslide deformation monitoring systems: Growth and evolution

B Ganesh, S Vincent, S Pathan, SRG Benitez - … Applications: Society and …, 2023 - Elsevier
Ongoing landslides have wreaked havoc in various regions across the globe. This article
presents a study of two forms of landslide monitoring viz; creation of Landslide Susceptibility …

Recent development of metal-organic frameworks and their composites in electromagnetic wave absorption and shielding applications

K Wei, Y Shi, X Tan, M Shalash, R Ren… - Advances in Colloid and …, 2024 - Elsevier
With the rapid development of information and communication industries, the usage of
electromagnetic waves has caused the hazard of human health and misfunction of devices …

An anthracene-based hydrogen-bonded organic framework as a bifunctional fluorescent sensor for the detection of γ-aminobutyric acid and nitrofurazone

Y Liu, X Xu, B Yan - Inorganic Chemistry Frontiers, 2022 - pubs.rsc.org
Intelligent fluorescence detection for disease diagnosis has become a research hotspot. In
the era of big data, machine learning (ML) for analyzing data and mining will be widely used …

Integrating deep learning neural network and M5P with conventional statistical models for landslide susceptibility modelling

S Saha, A Saha, M Santosh, B Kundu, R Sarkar… - Bulletin of Engineering …, 2024 - Springer
Landslides are among the devastating geological hazards that cause immense damage in
hilly regions. The Indian Himalayan region is plagued by numerous major landslides. Here …

Integration of GIS and machine learning techniques for mapping the landslide-prone areas in the state of Goa, India

B Ganesh, S Vincent, S Pathan… - Journal of the Indian …, 2023 - Springer
A landslide susceptibility map (LSM) assists in reducing the danger of landslides by locating
the landslide-prone locations within the designated area. One of the locations that are prone …

Improving the performance of artificial intelligence models using the rotation forest technique for landslide susceptibility mapping

H Shen, F Huang, X Fan, H Shahabi, A Shirzadi… - International Journal of …, 2023 - Springer
Landslide susceptibility assessment has always been the focus of landslide spatial
prediction research. In the present study, Muchuan County was selected as the study area …

[HTML][HTML] Hybridizing genetic random forest and self-attention based CNN-LSTM algorithms for landslide susceptibility mapping in Darjiling and Kurseong, India

A Moghimi, C Singha, M Fathi, S Pirasteh… - Quaternary Science …, 2024 - Elsevier
Landslides are a prevalent natural hazard in West Bengal, India, particularly in Darjeeling
and Kurseong, resulting in substantial socio-economic and physical consequences. This …

Enhancing co-seismic landslide susceptibility, building exposure, and risk analysis through machine learning

A Pyakurel, D KC, BK Dahal - Scientific reports, 2024 - nature.com
Landslides are devastating natural disasters that generally occur on fragile slopes.
Landslides are influenced by many factors, such as geology, topography, natural drainage …

Sugar-Based Phase-Selective Supramolecular Self-Assembly System for Dye Removal and Selective Detection of Cu2+ Ions

PV Bhavya, K Soundarajan, JG Malecki… - ACS …, 2022 - ACS Publications
Simple, effective, and eco-friendly sugar-based phase-selective gelators were synthesized
at a low cost. They showed high gelling ability toward a wide range of solvents at lower …

Assessment of resampling methods on performance of landslide susceptibility predictions using machine learning in Kendari City, Indonesia

S Aldiansyah, F Wardani - Water Practice & Technology, 2024 - iwaponline.com
Landslide susceptibility projections that rely on independent models produce biased results.
This situation will worsen class balance if working with a small population. This study …