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A novel ensemble learning based on Bayesian Belief Network coupled with an extreme learning machine for flash flood susceptibility mapping.

A. Shirzadi, S. Asadi, H. Shahabi, S. Ronoud, J. Clague, K. Khosravi, B. Pham, B. Ahmad, and D. Bui. Eng. Appl. Artif. Intell., (2020)

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Rouhollah Shahabi

Joachim Himanek

Other publications of authors with the same name

A novel hybrid machine learning approach for δ13C spatial prediction in polish hard-water lakes.H. Shahabi, A. Shirzadi, A. Ustrzycka, N. Piotrowska, J. Filipiak, and M. Tahan. Ecol. Informatics, (2025)Performance Evaluation and Comparison of Bivariate Statistical-Based Artificial Intelligence Algorithms for Spatial Prediction of Landslides.W. Chen, Z. Sun, X. Zhao, X. Lei, A. Shirzadi, and H. Shahabi. ISPRS Int. J. Geo Inf., 9 (12): 696 (2020)Hybrid Computational Intelligence Methods for Landslide Susceptibility Mapping.G. Wang, X. Lei, W. Chen, H. Shahabi, and A. Shirzadi. Symmetry, 12 (3): 325 (2020)Swarm intelligence optimization of the group method of data handling using the cuckoo search and whale optimization algorithms to model and predict landslides.A. Jaafari, M. Panahi, D. Gholami, O. Rahmati, H. Shahabi, A. Shirzadi, S. Lee, D. Bui, and B. Pradhan. Appl. Soft Comput., (2022)A comprehensive investigation of the causes of drying and increasing saline dust in the Urmia Lake, northwest Iran, via ground and satellite observations, synoptic analysis and machine learning models.N. Hamzeh, K. Shukurov, K. Mohammadpour, D. Kaskaoutis, A. Saadatabadi, and H. Shahabi. Ecol. Informatics, (December 2023)Fuzzy Shannon Entropy: A Hybrid GIS-Based Landslide Susceptibility Mapping Method.M. Roodposhti, J. Aryal, H. Shahabi, and T. Safarrad. Entropy, 18 (10): 343 (2016)Erratum: Dieu, T.B. et al. A Novel Integrated Approach of Relevance Vector Machine Optimized by Imperialist Competitive Algorithm for Spatial Modeling of Shallow Landslides. Remote Sens. 2018, 10, 1538.D. Bui, H. Shahabi, A. Shirzadi, K. Chapi, N. Hoang, B. Pham, Q. Bui, C. Tran, M. Panahi, B. Ahmad and 1 other author(s). Remote. Sens., 11 (1): 57 (2019)A novel hybrid integration model using support vector machines and random subspace for weather-triggered landslide susceptibility assessment in the Wuning area (China)H. Hong, J. Liu, A. Zhu, H. Shahabi, B. Pham, W. Chen, B. Pradhan, and D. Bui. Environmental Earth Sciences, (2017)A novel ensemble learning based on Bayesian Belief Network coupled with an extreme learning machine for flash flood susceptibility mapping.A. Shirzadi, S. Asadi, H. Shahabi, S. Ronoud, J. Clague, K. Khosravi, B. Pham, B. Ahmad, and D. Bui. Eng. Appl. Artif. Intell., (2020)Landslide Detection and Susceptibility Mapping by AIRSAR Data Using Support Vector Machine and Index of Entropy Models in Cameron Highlands, Malaysia.D. Bui, H. Shahabi, A. Shirzadi, K. Chapi, M. Alizadeh, W. Chen, A. Mohammadi, B. Ahmad, M. Panahi, H. Hong and 1 other author(s). Remote. Sens., 10 (10): 1527 (2018)

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Disambiguation of "Shahabi, Himan"

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A novel ensemble learning based on Bayesian Belief Network coupled with an extreme learning machine for flash flood susceptibility mapping.

Please choose a person to relate this publication to

Rouhollah Shahabi

Joachim Himanek

Other publications of authors with the same name

Disambiguation

BibSonomy

Disambiguation of "Shahabi, Himan"

copydeleteadd this publication to your clipboardcommunity posthistory of this postURLDOIBibTeXEndNoteAPAChicagoDIN 1505HarvardMSOffice XML A novel ensemble learning based on Bayesian Belief Network coupled with an extreme learning machine for flash flood susceptibility mapping.

Please choose a person to relate this publication to

Rouhollah Shahabi

Joachim Himanek

Other publications of authors with the same name

Disambiguation

copy delete add this publication to your clipboard
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URL
DOI
BibTeX
EndNote
APA
Chicago
DIN 1505
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A novel ensemble learning based on Bayesian Belief Network coupled with an extreme learning machine for flash flood susceptibility mapping.