In the proposed method, SVR forecasts rainfall of landslides on the Apache Spark platform. Apache Spark can carry out parallel in-memory large-scale data processing. Compared with other methods, the results provide the smallest root mean square error (RMSE) for rainfall forecasting of landslides.
In this research forecasting weather parameters as a variable for predicting the amount of rainfall using the ANFIS method and Support Vector Regression (SVR) ...
In the proposed method, SVR forecasts rainfall of landslides on the Apache Spark platform using support vector regression and provides the smallest root ...
Objective: The paper aims in presenting a prediction model by using Support Vector Machine (SVM) technique which is meant to possess a strong capability to ...
Abstract. Objective: The paper aims in presenting a prediction model by using Support Vector Machine (SVM) technique which is meant to possess a strong ...
Missing: Regression. | Show results with:Regression.
This paper presents a review of landslide susceptibility mapping using SVM. It presents the basic concept of SVM and its application in landslide ...
Missing: Rainfall | Show results with:Rainfall
Findings: The study concludes that SVM proved to be an efficient technique to forecast the landslides by predicting the rainfall in advance. The comparative ...
The predictions of rainfall extreme and their Impact on landslide susceptibility were evaluated, compared, and discussed.
Jan 1, 2023 · In this study, a hybrid method is utilized to predict rainfall-induced landslides. The proposed method combines support vector regression (SVR) ...
Jun 18, 2024 · We constructed a regional rainfall-induced landslides (RIL) probability forecasting model based on machine learning (ML) algorithms and divided warning levels.