Combining logistic regression-based hybrid optimized machine learning algorithms with sensitivity analysis to achieve robust landslide susceptibility mapping

Geocarto International, Год журнала: 2021, Номер 37(25), С. 9518 - 9543

Опубликована: Дек. 24, 2021

Landslides and other catastrophic environmental disasters pose a significant danger to environmental, infrastructure, people's lives. This research aimed construct four optimized ensemble machine learning algorithms for landslide susceptibility (LS) mapping, namely particle swarm optimization (PSO) based artificial neural network (ANN), random forest, M5P, support vector machine. The logistic regression (LR) model was then applied the four-ensemble generated hybrid model. receiver operating characteristics (ROC) curve used validate LS map. best of models depending on ROC's area under (AUC) is PSO-ANN (AUC-0.958) Also, LR model-based achieved better accuracy (AUC: 0.962) than Various resources, viz. grassland, built-up, scarce foliage, are declared as risk zones. Finally, elevation, soil-texture, slope, rainfall, road distance considered most sensitive parameters occurrences.

Язык: Английский

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A machine learning approach in spatial predicting of landslides and flash flood susceptible zones for a road network

Modeling Earth Systems and Environment, Год журнала: 2022, Номер 8(4), С. 4341 - 4357

Опубликована: Апрель 18, 2022

Язык: Английский

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Integrated deep learning with explainable artificial intelligence for enhanced landslide management

Natural Hazards, Год журнала: 2023, Номер 120(2), С. 1343 - 1365

Опубликована: Окт. 24, 2023

Язык: Английский

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Investigation of rainfall-induced landslide on unsaturated lateritic residual soil slope in Nilgiris, Western Ghats, India using deterministic and reliability analysis

Bulletin of Engineering Geology and the Environment, Год журнала: 2024, Номер 83(6)

Опубликована: Май 11, 2024

Язык: Английский

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Assessing the effect of future landslide on ecosystem services in Aqabat Al-Sulbat region, Saudi Arabia

Natural Hazards, Год журнала: 2022, Номер 113(1), С. 641 - 671

Опубликована: Март 29, 2022

Язык: Английский

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