›› 2006, Vol. 27 ›› Issue (S1): 822-825.

• Fundamental Theroy and Experimental Research • Previous Articles     Next Articles

Predicting model of vertical ultimate bearing capacity of single pile using adaptive neuro-fuzzy inference system

YANG Lei，XU Hong-zhong   

  1. College of Civil Engineering , Nanjing University of Technology, Nanjing 210009, China
  • Received:2006-05-10 Published:2006-12-15

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Abstract: Artificial neural networks have been used in many areas in geotechnical engineering applications. Adaptive neuro-fuzzy inference system (ANFIS) is used to predict vertical ultimate bearing capacity of single pile. The data of pile load test obtained from a literature are used to train ANFIS network and to determine the network parameters. The results show that the proposed modeling approach outperforms classical back-propagation (BP) neural network in terms of computational speed, forecast errors, efficiency. ANFIS is an effective method to achieve both high accuracy and less computational complexity for predicting vertical ultimate bearing capacity.

Key words: single pile, vertical ultimate bearing capacity, ANFIS, predicting model

CLC Number: 

  • TU 473
  • Please send e-mail to pingzhou3@126.com if you would like to read full paper in English for free. Parts of our published papers have English translations.
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