Volume 34 (2024)
Volume 33 (2023)
Volume 32 (2022)
Volume 31 (2021)
Volume 30 (2020)
Volume 29 (2020)
Volume 28 (2019)
Volume 27 (2018)
Volume 26 (2017)
Volume 25 (2016)
Volume 24 (2015)
Volume 23 (2014)
Volume 22 (2013)
Volume 21 (2012)
Volume 20 (2011)
Volume 19 (2010)
Volume 18 (2009)
Volume 17 (2008)
Volume 16 (2007)
Dynamic Modeling of Land Subsidence in Tehran Plain

S Angornai; H Memarian; M Shariat Panahi; M.J Bolourchi

Volume 25, Issue 97 , December 2016, , Pages 211-220

https://doi.org/10.22071/gsj.2015.41506

Abstract
  Land subsidence is an environmental phenomenon that involves gradual or sudden settlement of the land surface because of compaction of underground material. Groundwater withdrawal, which occurs due to excessive use of water resources, is among the most important reasons for this phenomenon. Therefore, ...  Read More

Estimation of Geodetic Virtual Velocity Based On Back Propagation Artificial Neural Networks (Case Study: NW Iran)

o Memarian Sorkhabi; Y Djamour

Volume 24, Issue 95 , June 2015, , Pages 69-76

https://doi.org/10.22071/gsj.2015.42155

Abstract
  In order to study the crustal movements in Iran, establishment of several campaign GPS networks in 1998 seriously initiated geodynamical activities. After that in 2005, a network of ~120 permanent GPS stations named Iranian Permanent GPS Network (IPGN) has been installed to complete the campaign GPS ...  Read More

Separating the Sungun Copper Deposit Alteration Zones by Applying Artificial Neural Network

A. Hezarkhani; P. Tahmasbi; O. Asghari

Volume 20, Issue 77 , January 2010, , Pages 41-46

https://doi.org/10.22071/gsj.2010.55304

Abstract
  Separation of alteration zones is one of the important processes in evaluation and identification of mining activities that provide great help to have better view of the region and its mineralization. Most of the alteration separation is based on petrological investigations and the other methods are ...  Read More

An Investigation on the Possibility of Two-Dimensional Joint Inversion of TE and TM Modes Data in Magnetotelluric (MT) Survey using Artificial Neural Network

A. Moradzadeh; F. Tahmasbi; M. Fateh

Volume 16, Issue 64 , March 2007, , Pages 88-101

https://doi.org/10.22071/gsj.2008.58218

Abstract
         The magnetotelluric (MT) method is a natural source electromagnetic geophysical technique, which is used mainly in petroleum, mineral and geothermal exploration. As in this method, the quantity of the measured data is bulky and have a complex structure, their modeling, ...  Read More