Volume 15 (2024)
Volume 14 (2023)
Volume 13 (2022)
Volume 12 (2021)
Volume 11 (2020)
Volume 10 (2019)
Volume 9 (2018)
Volume 8 (2017)
Volume 7 (2016)
Volume 6 (2015)
Volume 5 (2014)
Volume 4 (2013)
Volume 3 (2012)
Volume 2 (2011)
Volume 1 (2010)
Performance Comparison of Particle Swarm Optimization and Genetic Algorithm for Back-analysis of Soil Layer Geotechnical Parameters

Leila Nikakhtar; Shokroallah Zare; Hossein Mirzaei

Volume 14, Issue 1 , January 2023, , Pages 217-232

https://doi.org/10.22044/jme.2023.12452.2260

Abstract
  Surface settlement induced by tunneling is one of the most crucial problems in urban environments. Hence, accurate prediction of soil geotechnical properties is an important prerequisite in the minimization of it. In this research work, the amount of surface settlement is predicted using three-dimensional ...  Read More

Optimizing Extreme Learning Machine Algorithm using Particle Swarm Optimization to Estimate Iron Ore Grade

M. Fathi; A. Alimoradi; H.R. Hemati Ahooi

Volume 12, Issue 2 , April 2021, , Pages 397-411

https://doi.org/10.22044/jme.2021.10368.1984

Abstract
  Scientific uncertainties make the grade estimation very complicated and important in the metallic ore deposits. This paper introduces a new hybrid method for estimating the iron ore grade using a combination of two artificial intelligence methods; it is based on the single layer-extreme learning machine ...  Read More

Rock Mechanics
Predicting Unconfined Compressive Strength of Intact Rock Using New Hybrid Intelligent Models

M. Rezaei; M. Asadizadeh

Volume 11, Issue 1 , January 2020, , Pages 231-246

https://doi.org/10.22044/jme.2019.8839.1774

Abstract
  Bedrock unconfined compressive strength (UCS) is a key parameter in designing thegeosciences and building related projects comprising both the underground and surface rock structures. Determination of rock UCS using standard laboratory tests is a complicated, expensive, and time-consuming process, which ...  Read More

Using a combination of genetic algorithm and particle swarm optimization algorithm for GEMTIP modeling of spectral-induced polarization data

F. Sharifi; A.R. Arab Amiri; A. Kamkar Rouhani

Volume 10, Issue 2 , April 2019, , Pages 493-505

https://doi.org/10.22044/jme.2019.7902.1655

Abstract
  The generalized effective-medium theory of induced polarization (GEMTIP) is a newly developed relaxation model that incorporates the petro-physical and structural characteristics of polarizable rocks in the grain/porous scale to model their complex resistivity/conductivity spectra. The inversion of the ...  Read More

Rock Mechanics
A comparative study of two meta-heuristic algorithms in optimizing cost of reinforced concrete segmental lining

Seyed S. Mousavi; M. Nikkhah; Sh. Zare

Volume 10, Issue 1 , January 2019, , Pages 95-112

https://doi.org/10.22044/jme.2018.7159.1566

Abstract
  In this work, we tried to automatically optimize the cost of the concrete segmental lining used as a support system in the case study of Mashhad Urban Railway Line 2 located in NE Iran. Two meta-heuristic optimization methods including particle swarm optimization (PSO) and imperialist competitive algorithm ...  Read More

Joint inversion of ReMi dispersion curves and refraction travel times using particle swarm optimization algorithm

A. Zarean; R. Poormirzaee

Volume 7, Issue 1 , January 2016, , Pages 67-79

https://doi.org/10.22044/jme.2016.492

Abstract
  Shear-wave velocity ( ) is an important parameter used for site characterization in geotechnical engineering. However, dispersion curve inversion is challenging for most inversion methods due to its high non-linearity and mix-determined trait. In order to overcome these problems, in this study, a joint ...  Read More