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- W3148311789 abstract "The present study focuses on predicting the transient response of a strip footing with the help of adaptive neuro-fuzzy inference system (ANFIS). First, the data set is generated using a numerical model for 108 number of possible conditions varying the soil and loading parameters, using Open System for Earthquake Engineering Simulation (OpenSEES). The input parameters are factor of safety (FS), embedment ratio (Df/B), the intensity of cyclic load (qd(max)), and relative density of the soil (Dr, %). The output is (sf/su) %, i.e. the settlement due to the first load cycle (transient settlement, sf) divided by settlement (su) corresponding to the ultimate bearing capacity (qu) of the foundation. This data set is analyzed using ANFIS. 75% of the entire data was considered for the training and remaining for testing. The study reveals that the transient response of the foundation is significantly affected by the static load on the foundation. The outcomes from the sensitivity analysis of the trained ANFIS model will be helpful in designing foundations in industrial areas." @default.
- W3148311789 created "2021-04-13" @default.
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- W3148311789 date "2021-01-01" @default.
- W3148311789 modified "2023-09-24" @default.
- W3148311789 title "Transient Response Prediction of Shallow Foundation Using ANFIS" @default.
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- W3148311789 doi "https://doi.org/10.1007/978-981-33-4001-5_34" @default.
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