Machine summary:
From the beginning of the 1970s, the interest of both geoscientists and engineering professionals in LS zonation and the increasing emphasis on the use of Geographic Information Systems (GIS) technology led to the development of many methods such as weights-of-evidence model (Karami, 2012; Wang, Guo, Li, He, & Wu, 2019) logistic regression (Pham, Pradhan, Bui, Prakash, & Dholakia, 2016; Raja, Çiçek, Türkoğlu, Aydin, & Kawasaki, 2017), artificial neural networks neuro-fuzzy ,(٢٠١٤ ,Benardos &Tsangaratos ؛٢٠١٠ ,Chauhan, Sharma, Arora, Gupta) (Aghdam, Varzandeh, & Pradhan, 2016; Lee, Hong, & Jung, 2017; Chen et al.
مطالعه موردی:حوزه آبخیز سیمره )GIS لغزش در محیط بندی حساسیت زمین عصبی و تراکم سطح در ارزیابی کمی و پهنه A comparison of fuzzy analytic hierarchy process, artificial neural network and area] (هرمیان density in quantitative evaluation and landslide susceptibility mapping within GIS framework (Case Study: Simereh Homiyan watershed].
2. Materials and Methods In this study, firstly, the factors affecting landslide occurrence (including slope, aspect, lithology, land use, soil, precipitation, distance from the road, distance from the river and distance from fault), according to the natural and human conditions of the area were identified.
Weight Consistency Evaluation and Exploratory Factor Analysis of Urban Resilience from the Perspective of the Earthquake Crisis (Case study of Ilam city) a* Elias Mavedat a Assistant Professor in Urbanization, Jundi-Shapur University of Technology, Dezful, Iran Received: 2 January 2019 Accepted: 4 September 2019 1.
R Evaluation of economic and institutional resilience of urban communities] محلـه های شـهر تهـران against natural disasters, Case study: Tehran neighborhood earthquake].