An ANFIS Based Model for Predicting Frost Heaving in Seasonal Frozen Regions

Abstract:

An adaptive neuro-fuzzy inference system (ANFIS) model has been developed to predict frost heaving in seasonal frozen regions. The structure of ANFIS is initialized by the subtractive clustering algorithm. The hybrid learning algorithm consisting of back-propagation and least-squares estimation is used to adjust parameters of ANFIS and automatically produce fuzzy rules. The data of frost heaving test obtained from a literature are used to train and check the system. The predicted results show that the proposed model outperforms the back propagation neural network (BPNN) in terms of computational speed, forecast errors, and efficiency. The ANFIS based model proves to be an effective approach to achieve both high accuracy and less computational complexity for predicting frost heaving.

• Periodical: Applied Mechanics and Materials (Volumes 501-504)
• Pages: 391-394
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.501-504.391
• Online since: January 2014
• Authors: Yi Ming Xiang*, Xue Yan Liu, Gui Xiang Ling, Bin Du
• Keywords: Adaptive Network-Based Fuzzy Inference System, Frost Heaving, Hybrid Learning Algorithm, Subtractive Clustering Algorithm

References

[1] Tang Shuchun, Application of Fuzzy Mathematics in Frost Heaving Forecast of Foundation Soil, Oilfield Surface Engineering(OSE), vol. 12(2), p.65–68, April 1993 (In Chinese).

[2] Xu Kun and Yang Gengshe, Application of Comprehensive Fuzzy Evaluation Model in Frost Heaving Forecast, Chinese Journal of Rock Mechanics and Engineering, vol. 23 by 1, p.4339–4342, April 2004 (In Chinese).

[3] Qi Changqing, Wu Qingbai, Shi Bin, Wu Jimin and Yu Jin, Application of BP Neural Network on Deformation Prediction for Permafrost Embankment, Hydrogeology and Engineering Geology, vol. 4, p.27–30, April 2007 (In Chinese).

[4] Sun Shukui and Zhang Shuguang, Prediction of frost heave in soil based on fractal and neural network, Journal of Liaoning Technical University, vol. 26(6), p.874–876, December 2007 (In Chinese).

[5] Jang J.S.R., ANFIS: Adaptive-Network-Based Fuzzy Inference System, IEEE Transaction on Systems, Man and Cybernetics, vol. 2(3), p.665–685, May/Jun (1993).

DOI: 10.1109/21.256541

[6] Takagi T and Sugeno M., Fuzzy Identification of Systems and Its Applications to Modeling and Control, IEEE Trans. on SMC, (1985).

[7] Chiu S., Fuzzy Model Identification Based on Cluster Estimation, Journal of Intelligent and Fuzzy Systems, vol. 2(3), pp.267-278, (1994).

DOI: 10.3233/ifs-1994-2306

[8] Chen Xiaobai and Wang Yaqing, A New Model of Frost Heave Prediction for Clayer Soils, Science In China (Series B), vol. 34(10), October 1991 (In Chinese).