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Saha, Sunil, Saha, Anik, Santosh, M., Kundu, Barnali, Sarkar, Raju, Hembram, Tusar Kanti (2024) Integrating deep learning neural network and M5P with conventional statistical models for landslide susceptibility modelling. Bulletin of Engineering Geology and the Environment, 83 (1) doi:10.1007/s10064-023-03498-5

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Reference TypeJournal (article/letter/editorial)
TitleIntegrating deep learning neural network and M5P with conventional statistical models for landslide susceptibility modelling
JournalBulletin of Engineering Geology and the Environment
AuthorsSaha, SunilAuthor
Saha, AnikAuthor
Santosh, M.Author
Kundu, BarnaliAuthor
Sarkar, RajuAuthor
Hembram, Tusar KantiAuthor
Year2024 (January)Volume83
Issue1
PublisherSpringer Science and Business Media LLC
DOIdoi:10.1007/s10064-023-03498-5Search in ResearchGate
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Mindat Ref. ID17021569Long-form Identifiermindat:1:5:17021569:7
GUID0
Full ReferenceSaha, Sunil, Saha, Anik, Santosh, M., Kundu, Barnali, Sarkar, Raju, Hembram, Tusar Kanti (2024) Integrating deep learning neural network and M5P with conventional statistical models for landslide susceptibility modelling. Bulletin of Engineering Geology and the Environment, 83 (1) doi:10.1007/s10064-023-03498-5
Plain TextSaha, Sunil, Saha, Anik, Santosh, M., Kundu, Barnali, Sarkar, Raju, Hembram, Tusar Kanti (2024) Integrating deep learning neural network and M5P with conventional statistical models for landslide susceptibility modelling. Bulletin of Engineering Geology and the Environment, 83 (1) doi:10.1007/s10064-023-03498-5
In(2024, January) Bulletin of Engineering Geology and the Environment Vol. 83 (1) Springer Science and Business Media LLC

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Saha, Sunil, Saha, Anik, Roy, Bishnu, Sarkar, Raju, Bhardwaj, Dhruv, Kundu, Barnali (2022) Integrating the Particle Swarm Optimization (PSO) with machine learning methods for improving the accuracy of the landslide susceptibility model. Earth Science Informatics, 15 (4) 2637-2662 doi:10.1007/s12145-022-00878-5
Saha, Sunil, Saha, Anik, Roy, Bishnu, Sarkar, Raju, Bhardwaj, Dhruv, Kundu, Barnali (2023) Correction to: Integrating the Particle Swarm Optimization (PSO) with machine learning methods for improving the accuracy of the landslide susceptibility model. Earth Science Informatics, 16 (3) 2987-2990 doi:10.1007/s12145-023-01030-7
Saha, Sunil, Saha, Anik, Roy, Bishnu, Sarkar, Raju, Bhardwaj, Dhruv, Kundu, Barnali (2022) Correction to: Integrating the Particle Swarm Optimization (PSO) with machine learning methods for improving the accuracy of the landslide susceptibility model. Earth Science Informatics, 15 (4) 2663-2664 doi:10.1007/s12145-022-00892-7
Saha, Sunil, Saha, Anik, Hembram, Tusar Kanti, Mandal, Kanu, Sarkar, Raju, Bhardwaj, Dhruv (2022) Prediction of spatial landslide susceptibility applying the novel ensembles of CNN, GLM and random forest in the Indian Himalayan region. Stochastic Environmental Research and Risk Assessment, 36 (10) 3597-3616 doi:10.1007/s00477-022-02212-3
Saha, Sunil, Barman, Aparna, Saha, Anik, Hembram, Tusar K., Pradhan, Biswajeet, Alamri, Abdullah (2024) Deep learning algorithms based landslide vulnerability modeling in highly landslide prone areas of Tamil Nadu, India. Geosciences Journal, 28 (6). doi:10.1007/s12303-024-0044-y
Saha, Sunil, Roy, Jagabandhu, Pradhan, Biswajeet, Hembram, Tusar Kanti (2021) Hybrid ensemble machine learning approaches for landslide susceptibility mapping using different sampling ratios at East Sikkim Himalayan, India. Advances in Space Research, 68 (7) 2819-2840 doi:10.1016/j.asr.2021.05.018
Hembram, Tusar kanti, Paul, Gopal Chandra, Saha, Sunil (2019) Spatial prediction of susceptibility to gully erosion in Jainti River basin, Eastern India: a comparison of information value and logistic regression models. Modeling Earth Systems and Environment, 5. 689-708 doi:10.1007/s40808-018-0560-8
Saha, Sunil, Kundu, Barnali, Saha, Anik, Mukherjee, Kaustuv, Pradhan, Biswajeet (2023) Manifesting deep learning algorithms for developing drought vulnerability index in monsoon climate dominant region of West Bengal, India. Theoretical and Applied Climatology, 151 (1) 891-913 doi:10.1007/s00704-022-04300-4
Saha, Sunil, Kundu, Barnali, Paul, Gopal Chandra, Pradhan, Biswajeet (2023) Proposing an ensemble machine learning based drought vulnerability index using M5P, dagging, random sub-space and rotation forest models. Stochastic Environmental Research and Risk Assessment, 37 (7) 2513-2540 doi:10.1007/s00477-023-02403-6
Chen, Wei, Yang, Zifan (2023) Landslide susceptibility modeling using bivariate statistical-based logistic regression, naïve Bayes, and alternating decision tree models. Bulletin of Engineering Geology and the Environment, 82 (5) doi:10.1007/s10064-023-03216-1
Wu, Bin, Shi, Zhenming, Zheng, Hongchao, Peng, Ming, Meng, Shaoqiang (2024) Impact of sampling for landslide susceptibility assessment using interpretable machine learning models. Bulletin of Engineering Geology and the Environment, 83 (11). doi:10.1007/s10064-024-03980-8
 
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