Because of the increasing popularity worldwide of the cone penetration test (CPT) for site characterization, significant progress on the simplified CPT-based methods has been made for evaluation of earthquake induced liquefaction potential of soils. In this study, a fuzzy-neural network combined with 466 CPT field observations is developed to evaluate liquefaction potential of soils. The proposed model combines fuzzy theory with subtractive clustering algorithm to establish a fuzzy-neural system. The study indicates that fuzzy-neural network can successfully describe the complex relationship between seismic parameters, soil parameters, and the liquefaction potential. The fuzzy-neural network model is found to have very good predictive ability and is expected to be very reliable for evaluation of liquefaction potential.
Chern, Shuh-Gi; Lee, Ching-Yinn; and Wang, Chin-Chen
"CPT-BASED LIQUEFACTION ASSESSMENT BY USING FUZZY-NEURAL NETWORK,"
Journal of Marine Science and Technology: Vol. 16:
2, Article 6.
Available at: https://jmstt.ntou.edu.tw/journal/vol16/iss2/6