In this study, a fuzzy adaptive network “Fuzz-ART”, based on adaptive resonance theory (ART) combined with fuzzy set theory is developed to evaluate liquefaction potentials induced by Chi-Chi earthquake in Yuan-Lin area. The proposed system combines the backpropagation algorithm for parameter learning and the fuzzy ART algorithm for structure learning. With the help of case studies, it is shown that the “Fuzz-ART” network is able to predict liquefaction potentials much more satisfactorily than conventional artificial neural network methods. If more data are collected, it may well evaluate liquefaction potentials induced by Chi-Chi earthquake.
Chern, S. G.; Hu, R. F.; Chang, Y. J.; and Tsai, I. F.
"Fuzzy-Art Neural Networks for Predicting Chi-Chi Earthquake Induced Liquefaction in Yuan-Lin Area,"
Journal of Marine Science and Technology: Vol. 10:
1, Article 4.
Available at: https://jmstt.ntou.edu.tw/journal/vol10/iss1/4