Predicting liquefaction-induced lateral spreading by using the multigene genetic programming (MGGP), multilayer perceptron (MLP), and random forest (RF) techniques
Yükleniyor...
Tarih
2023
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Springer Science and Business Media
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
Landslides refer to a wide range of processes that result in the downward and outward movement of slope-forming materials,
which may spread. Estimating lateral spreading of soil is essential because of the complexities associated with the lateral
spreading behavior. Existing empirical models for predicting liquefaction-induced lateral spread displacement are developed
using a dataset that varied in terms of earthquake magnitude, source distance, ground slope, layer thickness, fines content,
and grain size. The aim of this study is to increase the accuracy of earthquake-induced lateral spreading prediction using
multigene genetic programming (MGGP), multilayer perceptron (MLP), and random forest (RF) model. MGGP, MLP, and
RF model predictions of lateral spreading are compared with the results anticipated using machine learning techniques and
conventional approaches. Results showed that the MGGP outperforms the Hamada, Youd, MLP, and RF equations for estimating maximum lateral displacement under free-face and gently sloping ground conditions according to the comparisons.
The MGGP, which is proved to be better, was also utilized to estimate total lateral displacement for Adapazari data, along
with machine learning techniques and conventional approaches.
Açıklama
Anahtar Kelimeler
Lateral spreading, MGGP, MLP, RF, Kocaeli earthquake
Kaynak
Bulletin of Engineering Geology and the Environment
WoS Q Değeri
N/A
Scopus Q Değeri
Q1
Cilt
82
Sayı
3
Künye
Kaya, Z., Latifoğlu, L., Uncuoğlu, E., Erol, A. ve Keskin, M. S. (2023). Predicting liquefaction-induced lateral spreading by using the multigene genetic programming (MGGP), multilayer perceptron (MLP), and random forest (RF) techniques. Bulletin of Engineering Geology and the Environment, 82(3), 1-18.
