A comparative study between popular statistical and machine learning methods for simulating volume of landslides

by Shirzadi, A., Shahabi, H., Chapi, K., Bui, D. T., Pham, B. T., Shahedi, K., Ahmad, B. B.
Published 2017

A hybrid intelligence approach to enhance the prediction accuracy of local scour depth at complex bridge piers

by Bui, D. T., Shirzadi, A., Amini, A., Shahabi, H., Al-Ansari, N., Hamidi, S., Singh, S. K., Pham, B. T., Ahmad, B. B., Ghazvinei, P. T.
Published 2020

Novel GIS based machine learning algorithms for shallow landslide susceptibility mapping

by Shirzadi, A., Soliamani, K., Habibnejhad, M., Kavian, A., Chapi, K., Shahabi, H., Chen, W., Khosravi, K., Pham, B. T., Pradhan, B., Ahmad, A., Ahmad, B., Bui, D. T.
Published 2018

Landslide susceptibility modeling based on GIS and novel bagging-based Kernel logistic regression

by Chen, W., Shahabi, H., Zhang, S., Khosravi, K., Shirzadi, A., Chapi, K., Pham, B. T., Zhang, T., Zhang, L., Chai, H., Ma, J., Chen, Y., Wang, X., Li, R., Ahmad, B. B.
Published 2018

Gis-based gully erosion susceptibility mapping: a comparison of computational ensemble data mining models

by Nhu, V. H., Janizadeh, S., Avand, M., Chen, W., Farzin, M., Omidvar, E., Shirzadi, A., Shahabi, H., Clague, J. J., Jaafari, A., Mansoorypoor, F., Pham, B. T., Ahmad, B. B., Lee, S.
Published 2020

GIS based novel hybrid computational intelligence models for mapping landslide susceptibility: A case study at Da Lat City, Vietnam

by Nguyen V.-T., Tran T.H., Ha N.A., Ngo V.L., Nadhir A.-A., Tran V.P., Nguyen H.D., Malek M.A., Amini A., Prakash I., Ho L.S., Pham B.T.
Published 2023

Shallow landslide susceptibility mapping: a comparison between logistic model tree, logistic regression, nave bayes tree, artificial neural network, and support vector machine algo...

by Nhu, V. H., Shirzadi, A., Shahabi, H., Singh, S. K., Al-Ansari, N., Clague, J. J., Jaafari, A., Chen, W., Miraki, S., Dou, J., Luu, C., Górski, K., Pham, B. T., Nguyen, H. D., Ahmad, B. B.
Published 2020

Using GIS, remote sensing, and machine learning to highlight the correlation between the land-use/land-cover changes and flash-flood potential

by Costache R., Pham Q.B., Corodescu-Ro?ca E., C�mpianu C., Hong H., Thuy Linh N.T., Fai C.M., Ahmed A.N., Vojtek M., Pandhiani S.M., Minea G., Ciobotaru N., Popa M.C., Diaconu D.C., Pham B.T.
Published 2023