Titlebook: Geomorphic Risk Reduction Using Geospatial Methods and Tools; Raju Sarkar,Sunil Saha,Rajib Shaw Book 2024 The Editor(s) (if applicable) an

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Introduction to the Finite Element Method, deposition of sediments. People in Manikchak, Kaliachak-II, and Kaliachak-III blocks of Malda district West Bengal were highly affected due to this river shifting in the lower course of the Ganga River. A few portions of the Rajmahal block of Jharkhand, located on the right side of the river are also affected.

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Landslide Susceptibility Assessment Based on Machine Learning Techniquese datasets were recommended. A total of 9 machine learning methods applied in LSA were simply introduced. The advantages and future work of LSA based on machine learning techniques were summarized from the aspects of scale, performance, modeling, and interpretability.

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The Adoption of Random Forest (RF) and Support Vector Machine (SVM) with Cat Swarm Optimization (CSOs that would be used for both training and testing by using a random sampling technique. This allowed us to have complete control over the models. It was discovered that CSO not only improved the fitting of the model and the quality of the results, but it also speed up the procedure.

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Book 2024itional statistical methods and advanced machine learning methods and addresses the different ways to reduce the impact of geomorphic hazards..In recent years with the development of human infrastructures, geomorphic hazards are gradually increasing, which include landslides, flood and soil erosion,