Forecasting Surface Settlement Caused by Shield Tunneling Using ANN-BBO Model and ANFIS Based on Clustering Methods

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FATTAHI HADI; Bayatzadehfard Zohreh

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Paper Information

Journal: JOURNAL OF ENGINEERING GEOLOGY Year:2018 | Volume:12 | Issue:5 (supp.) Page(s): 55-84

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Title

Forecasting Surface Settlement Caused by Shield Tunneling Using ANN-BBO Model and ANFIS Based on Clustering Methods

Author(s)

FATTAHI HADI | Bayatzadehfard Zohreh | Issue Writer Certificate

Keywords

Maximum surface settlementsQ1

EPB shield tunnelingQ1

Adaptive networkbased fuzzy inference systemQ1

Artificial neural networkQ2

Biogeography-based optimization algorithmQ2

Abstract

Maximum surface settlement (MSS) is an important parameter for the design and operation of earth pressure balance (EPB) shields that should be determined before tunneling. Artificial intelligence (AI) methods are accepted as a technology that offers an alternative way to tackle highly complex problems that cannot be modeled in mathematics. They can learn from examples and they are able to handle incomplete data and noisy data. The adaptive network– based fuzzy inference system (ANFIS) and hybrid Artificial neural network (ANN) with Biogeography-based optimization algorithm (ANN-BBO) are kinds of AI systems that were used in this study to make a prediction model for the MSS caused by EPB shield tunneling. Two ANFIS models were implemented, the ANFIS-subtractive clustering method (ANFIS-SCM) and ANFIS-fuzzy c-means clustering method (ANFIS-FCM). The estimation abilities offered using three models were presented by using field data from the Bangkok Subway Project in Thailand. In these models, depth, distance from shaft, ground water level from tunnel invert, average face pressure, average penetrate rate, pitching angle, tail void grouting pressure and percent tail void grout filling were utilized as the input parameters, while the MSS was the output parameter. To compare the performance of models for MSS prediction, the coefficient of correlation (R2) and mean square error (MSE) of the models were calculated, indicating the good performance of the ANFIS-SCM model.

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APA: Copy

FATTAHI, HADI, & Bayatzadehfard, Zohreh. (2018). Forecasting Surface Settlement Caused by Shield Tunneling Using ANN-BBO Model and ANFIS Based on Clustering Methods. JOURNAL OF ENGINEERING GEOLOGY, 12(5 (supp.) ), 55-84. SID. https://sid.ir/paper/186323/en

Vancouver: Copy

FATTAHI HADI, Bayatzadehfard Zohreh. Forecasting Surface Settlement Caused by Shield Tunneling Using ANN-BBO Model and ANFIS Based on Clustering Methods. JOURNAL OF ENGINEERING GEOLOGY[Internet]. 2018;12(5 (supp.) ):55-84. Available from: https://sid.ir/paper/186323/en

IEEE: Copy

HADI FATTAHI, and Zohreh Bayatzadehfard, “Forecasting Surface Settlement Caused by Shield Tunneling Using ANN-BBO Model and ANFIS Based on Clustering Methods,” JOURNAL OF ENGINEERING GEOLOGY, vol. 12, no. 5 (supp.) , pp. 55–84, 2018, [Online]. Available: https://sid.ir/paper/186323/en

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