Candan Gokceoglu

TL;DR: In this paper, a spatial multi-criteria evaluation approach (SMCE) was used to estimate landslide susceptibility map in a landslide-prone area (Haraz) in Iran.

TL;DR: The results of laboratory experiments and numerical simulations conducted to estimate the uniaxial compressive strength of some clay-bearing rocks selected from Turkey show that the performance of capacities of proposed NN model is quite satisfactory, however, the NN models including four cycle slake durability index yielded slightly more precise results than that including two cycle slakes durability index.

TL;DR: This study investigates the performances of landslide susceptibility maps produced with three different machine learning algorithms in a recently constructed and activated dam reservoir and assess the external quality of each map by using pre- and post-event photogrammetric datasets.

TL;DR: It is concluded that both constructed models exhibited a high performance according to the obtained prediction values, and the prediction performance of the nonlinear multiple regression model is higher than that of the fuzzy inference system model.

TL;DR: In this paper, the authors proposed a severity index for the preparation of susceptibility maps, which can be used in earthquake geotechnical engineering, and applied to two sites from Taiwan (Yuanlin) and Turkey (Inegol) to examine performance.