Ditapis dengan
A Probability-Based Framework for Evaluating Slope Failure Under Rainfall Usi…
Rainfall is one of the major causes of geological hazards such as landslides and slope failures because it decreases shear strength along the failure surface and increases the driving force of the sliding mass due to the movement of the wetting front in the geological media. Deterministic limit equilibrium methods are typically used to evaluate the stability of slopes in terms of Factor of Safe…
- Edisi
- Vol.15, Issue 4, April 2025
- ISBN/ISSN
- 2076-3263
- Deskripsi Fisik
- 25 hlm PDF, 3.340 KB
- Judul Seri
- Geosciences
- No. Panggil
- 550
The May 2023 Rainstorm-Induced Landslides in the Emilia-Romagna Region (North…
Rainstorm-induced landslides are a widespread geomorphological hazard that can lead to major emergencies, causing severe damage to life and property. Due to the extent of the areas usually affected by these phenomena (up to thousands of km2) and/or their typical high areal density, in the early stages of the emergency it can be useful to reconstruct a comprehensive, albeit preliminary, overview…
- Edisi
- Vol.15, Issue 3, March 2025
- ISBN/ISSN
- 2076-3263
- Deskripsi Fisik
- 24 hlm PDF, 7.048 KB
- Judul Seri
- Geosciences
- No. Panggil
- 550
Modeling ANN-Based Estimations of Probabilistic-Based Failure Soil Depths for…
In this study, an ANN-derived innovative model was developed for estimating the failure soil depths of rainfall-induced shallow landslide events, named the SM_EFD_LS model. The proposed SM_EFD_LS model was created using the modified ANN model via the genetic algorithm calibration approach (GA-SA) with multiple transfer functions (MTFs) (ANN_GA-SA_MTF) with a significant number of failure soil d…
- Edisi
- Vol.15, Issue 3, March 2025
- ISBN/ISSN
- 2076-3263
- Deskripsi Fisik
- 27 hlm PDF, 11.347 KB
- Judul Seri
- Geosciences
- No. Panggil
- 550
A combined deep CNN-RNN network for rainfall-runoff modelling in Bardha Water…
In recent years, there has been a growing interest in using artificial intelligence (AI) for rainfall-runoff modelling, as it has shown promising adaptability in this context. The current study involved the use of six distinct AI models to simulate monthly rainfall-runoff modelling in the Bardha watershed, India. These models included the artificial neural network (ANN), k-nearest neighbour reg…
- Edisi
- Vol.5, December 2024
- ISBN/ISSN
- 2666-5441
- Deskripsi Fisik
- 13 hlm PDF, 6.872 KB
- Judul Seri
- Artificial Intelligence in Geosciences
- No. Panggil
- 551
A convolutional recurrent neural network for strong convective rainfall nowca…
Strong convective systems and the associated heavy rainfall events can trig-ger floods and landslides with severe detrimental consequences. These events have a high spatio-temporal variability, being difficult to predict by standard meteorological numerical models. This work proposes the M5Images method for performing the very short-term prediction (nowcasting) of heavy convective rainfall usin…
- Edisi
- Vol.3, December 2022
- ISBN/ISSN
- 2666-5441
- Deskripsi Fisik
- 6 hlm PDF, 1.368 KB
- Judul Seri
- Artificial Intelligence in Geosciences
- No. Panggil
- 551
Evaluating Imputation Methods for rainfall data under high variability in Joh…
Missing values in rainfall records might result in erroneous predictions and inefficient management practices with significant economic, environmental, and social consequences. This is particularly important for rainfall datasets in Peninsular Malaysia (PM) due to the high level of missingness that can affect the inherent pattern in the highly variable time series. In this work, 21 target rainf…
- Edisi
- Vol.20, December 2023
- ISBN/ISSN
- 2590-1974
- Deskripsi Fisik
- 16 hlm PDF, 12.766 KB
- Judul Seri
- Applied Computing and Geoscience - Open Access
- No. Panggil
- 551.136
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