Recurrent landslide events triggered by typhoons and tropical storms over Vietnam pose a longstanding threat to the nation's population and infrastructure. Changes in hydroclimatic conditions, especially the growing intensity and frequency of storms,...
Environmental science and pollution research international
Apr 9, 2024
Landslide susceptibility mapping is essential for reducing the risk of landslides and ensuring the safety of people and infrastructure in landslide-prone areas. However, little research has been done on the development of well-optimized Elman neural ...
Environmental science and pollution research international
Dec 12, 2023
In the mountainous region of Asir region of Saudi Arabia, road construction activities are closely associated with frequent landslides, posing significant risks to both human life and infrastructural development. This highlights an urgent need for a ...
Environmental science and pollution research international
Nov 21, 2023
Detecting and mapping landslides are crucial for effective risk management and planning. With the great progress achieved in applying optimized and hybrid methods, it is necessary to use them to increase the accuracy of landslide susceptibility maps....
Environmental science and pollution research international
May 9, 2023
The western flanks of the Western Ghats are one of the major landslide hotspots in India. Recent rainfall triggered landslide incidents in this humid tropical region necessitating the accurate and reliable landslide susceptibility mapping (LSM) of se...
Environmental science and pollution research international
Feb 15, 2023
Differences in model application effectiveness, insufficient numbers of disaster samples, and unreasonable selection of non-hazard samples are common problems in landslide susceptibility studies. Therefore, in this paper, we propose a semi-integrated...
Computational intelligence and neuroscience
May 23, 2022
The power of wireless network sensor technologies has enabled the development of large-scale in-house monitoring systems. The sensor may play a big part in landslide forecasting where the sensor linked to the WLAN protocol can usefully map, detect, a...
We mapped landslide susceptibility in Kamyaran city of Kurdistan Province, Iran, using a robust deep-learning (DP) model based on a combination of extreme learning machine (ELM), deep belief network (DBN), back propagation (BP), and genetic algorithm...
The objective is to study the design method of roadway support and provide technical support for coal mining and other mining methods that need deep roadway excavation. Through literature review, the occurrence, development mechanism and influencing ...
International journal of environmental research and public health
Jul 8, 2020
We used AdaBoost (AB), alternating decision tree (ADTree), and their combination as an ensemble model (AB-ADTree) to spatially predict landslides in the Cameron Highlands, Malaysia. The models were trained with a database of 152 landslides compiled u...
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