Journal of
Civil Engineering and Construction Technology

  • Abbreviation: J. Civ. Eng. Constr. Technol.
  • Language: English
  • ISSN: 2141-2634
  • DOI: 10.5897/JCECT
  • Start Year: 2010
  • Published Articles: 139

Full Length Research Paper

Artificial neural networks in calculation of telecommunication towers natural frequency

Kaveh Kumarci* and Afsaneh Banitalebi Dehkordi
  Sama Technical and Vocational Training Collage, Islamic Azad University, Shahrekord Branch, Shahr-e-kord, Iran.
Email: [email protected]

  •  Accepted: 02 December 2010
  •  Published: 31 March 2011



The present paper presented the training or learning algorithms in telecommunication towers based on the artificial neural networks to calculate accurately their natural frequency in different supporting conditions. Using SAP2000 program, the real frequency is calculated and is defined as a goal function for neural network, so that all outputs of the network can be compared to this function and the error can be calculated. The inputs including dimensions or specifications of telecommunication towers are made in MATLAB environment. According to the presented results, the performance of the neural network is optimum, and the errors are less than 6%, so the network can perform training in different manner. Furthermore, compare with analysis time of SAP2000 software, the time of frequency calculations in neural network is very low the precision of 9% is recorded.


Key words: Natural frequency, artificial intelligence, telecommunication towers, training and learning algorithm.