Proceedings of the First Mandalika International Multi-Conference on Science and Engineering 2022, MIMSE 2022 (Civil and Architecture)

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Application of the Adaptive Neuro Fuzzy Inference System (ANFIS) to Predict Ultimate Bearing Capacity of Footing on Granular Soil

Authors
Ngudiyono1, *, Tri Sulistyowati1
1Department of Civil Engineering, University of Mataram, Mataram, Indonesia
*Corresponding author. Email: ngudiyono@unram.ac.id
Corresponding Author
Ngudiyono
Available Online 23 December 2022.
DOI
10.2991/978-94-6463-088-6_2How to use a DOI?
Keywords
footing; granular soil; ultimate bearing capacity; ANFIS
Abstract

The ultimate bearing capacity is an important parameter in the footing foundation design. Several classical methods are often used to analyze the bearing capacity of a footing foundation. However, the results of this analysis always give less accurate results than the experiment. In this manuscript, an Adaptive Neuro Fuzzy Inference System (ANFIS) model was built for predicting ultimate bearing capacity of footings on granular soil. Learning process data consists of input and output. The five input parameters used for the model development in this study are width (B), depth (Df), shape factor (L/B) of footing, unit weight (γ) and friction angle (ϕ) of soil and the output is ultimate bearing capacity (qu). The results of the analysis showed that the ANFIS model has a good level of accuracy compared with the experiment, where the correlation coefficient (R2) for testing data was 0.98 and the Root Mean Square Error (RMSE) was 32.11 kN/m2. This demonstrates that the ANFIS model developed is accurate in predicting the ultimate bearing capacity of footings on granular soil.

Copyright
© 2023 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title
Proceedings of the First Mandalika International Multi-Conference on Science and Engineering 2022, MIMSE 2022 (Civil and Architecture)
Series
Advances in Engineering Research
Publication Date
23 December 2022
ISBN
10.2991/978-94-6463-088-6_2
ISSN
2352-5401
DOI
10.2991/978-94-6463-088-6_2How to use a DOI?
Copyright
© 2023 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

risenwbib
TY  - CONF
AU  - Ngudiyono
AU  - Tri Sulistyowati
PY  - 2022
DA  - 2022/12/23
TI  - Application of the Adaptive Neuro Fuzzy Inference System (ANFIS) to Predict Ultimate Bearing Capacity of Footing on Granular Soil
BT  - Proceedings of the First Mandalika International Multi-Conference on Science and Engineering 2022, MIMSE 2022 (Civil and Architecture)
PB  - Atlantis Press
SP  - 3
EP  - 14
SN  - 2352-5401
UR  - https://doi.org/10.2991/978-94-6463-088-6_2
DO  - 10.2991/978-94-6463-088-6_2
ID  - 2022
ER  -