پهنه بندی خطر زمین لغزش با استفاده از مدلهای شبکه عصبی مصنوعی و تاپسیس در پایین دست سد سنندج

Amirahmadi, A., Naemi Tabar, M. & Golkar, B. (2017). Prioritization and zoning of factors affecting landslide occurrence using entropy model (Case study: Bajgiran area, ghouchan), Hydrogeomorphology, 3(11(105-152.

Claesen, M. & De moor, B. (2015). Hyperparameter search in machine learning. arXiv preprint arXiv, The XI Metaheuristics International Conference 1502.02127.

Dong, S. (2016). Comparisons between Different Multi-Criteria Decision Analysis techniques for Disease Susceptibility Mapping. Student Thesis Series INES. Department of Physical Geography and Ecosystem Science Lund University Sölvegatan. Sweden 12 S-223 62.

Emadadin, S & Moradi, A. (2016). Risk assessment of landslides using hierarchical analysis process and artificial neural network Field studies with risk reduction approach in Haraz road axis. Quantitative Geomorphological Research, 6(4), 190-172.

Geological Map Description Sanandaj 1: 1000000. (1990) Geological Survey if Iran. Tehran. Iran.

Jimenez-Peralvarez, J.D, EI Hamdouni, R., Palenzeuela., J, A., Irigaray, C & Chason, J. (2017). Landslide hazard mapping through multi-technique activity assessment: an example from the betic cordillera (southern Spain), Landslides, 14(6): 1975-1991.

Karam, A, (2007), Application of WLC Weight Linear Combination Model in Landslide Potential Zoning, Geography and Development Quarterly. (6) 131-146.

Lee, S, Lee M, J& Jung, H, S. (2017). Date mining approaches for Landslide Susceptibility Mapping in Umyeonsan, Seul, South Korea. Applied Sciences. 7(7). 683.

McCulloch, W. S. & W. Pitts (1990). A logical calculus of the ideas immanent in nervous activity. Bulletin of mathematical biology 52(1-2): 99-115.

Mirsanei, R & Mehdifar, M. (2006). Optimal Methods and Criteria for Landslade Hazard Mapping, Natural Disaster Research Institute. 1-27.

Naeri, R & Karami, M. (2018). Integration of Analytical Zoning Risk of Bijar Lanslade Occurrence, Journal of Engineering Geology, 12(1), 153-182.

Noshadi, M, Shahabi, H & Salari, M, (2018). On Topic Identification of Geomorphological Hazards of Indices in Piranshahr Road to Sardasht with Topsis Model. MSc in physical geography, Faculty of Natural resources, University of Kurdistan, 155p.

Razavi terme, V & Shirani, K, (2019). Landslide hazard zonation using frequency ratio, entropy method and TOPSIS scission making method in Fahliyan, Remote Sensing and Geographic Information Systems in Natural Resources. 9 (4), 119-138.

Neural Network Model in Landslide Risk Zoning of Aleshtar Basin. Geography and Planning (59).86-93.

Rosenfeld, C, L. (2004). Geomorphological Hazard, Encyclopedia of Geomorphology, (l).423-426.

Roustaei, SH, Valizadeh, K & Narimani, P. (2016). Evaluation of Artificial Intelligence Model and Multi Criteria Decision Modeling in Landslide Risk Mapping in Idoghmoush, M.Sc  in Geomorphology, Faculty of Geography and Planning, University of Tabriz.

Rahimpour, T., Roustaei SH. & Noxostin, M, (2017). Landslide hazard zoning using hierarchical analysis process and ArcGIS (Sardolchai watershed, Ardabil) Hydrogeomorphology. 3(13).1-20.

Taheri, V. Karam, A & Safari, A. (2019). Spreading and assessing the vulnerability caused by landslides in the mountainous basins of Golestan province. PHD in Geomorphology. University of kharazmi. Tehran, 138p.

Yamani, M, Ahmadabadi, A. & Zare, Gh. (2012). Assessing the efficiency of artificial intelligence techniques in landslide studies with emphasis on SVM algorithm. Geography and environmental hazards. 1(3). 125-142.

Van Westen, C.J., (1993). Application of Geographic Information Systems in Landslide Hazard Zonation. ITC publication, P15.

Wang, H.B, Li, J.M, Zhou, B Xhou, Y, Yuan, Z.Q, & Chen, Y.P. (2017). Application of a hybrid model of neural networks and genetic algorithms to evaluate landslide susceptibility, Geo environmental Disasters 4:15.