id	author	title	date	pages	extension	mime	words	sentence	flesch	summary	cache	txt
ajgt-4122	Anuragi, Saurabh Kumar; Kishan, D.	Landslide Prediction and Mapping through Geospatial and Neural Network Approach	2025	12	.pdf	application/pdf	5549	282	33	As a result, the MLPNN_logistic model is identified as the most reliable and effective tool for landslide susceptibility mapping in this study, rendering it an optimal choice for predictive analyses in this field. Khatun et al. (2022) employed a weighted overlay approach for landslide susceptibility mapping in Rangmati, Bangladesh, taking into account various conditioning factors such as soil texture, geology, lineament, slope, land use, and aspect.	cache/ajgt-4122.pdf	txt/ajgt-4122.txt