Developing a hybrid adoptive neuro-fuzzy inference system in predicting safety of factors of slopes subjected to surface
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ORIGINAL ARTICLE
Developing a hybrid adoptive neuro‑fuzzy inference system in predicting safety of factors of slopes subjected to surface eco‑protection techniques Puteri Azura Sari1 · Meldi Suhatril1 · Normaniza Osman2 · M. A. Mu’azu3 · Javad Katebi4 · Ali Abavisani5,6 · Naser Ghaffari7 · Esmaeil Sadeghi Chahnasir8 · Karzan Wakil9 · Majid Khorami10 · Dalibor Petkovic11 Received: 23 December 2018 / Accepted: 29 April 2019 © Springer-Verlag London Ltd., part of Springer Nature 2019
Abstract This study predicts the investigation of surface eco-protection techniques for cohesive soil slopes along the selected Guthrie Corridor Expressway stretch by way of analyzing a new set of probabilistic models using a hybrid technique of artificial neural network and fuzzy inference system namely adaptive neuro-fuzzy inference system (ANFIS). Soil erosion and mass movement which induce landslides have become one of the disasters faced in Selangor, Malaysia causing enormous loss affecting human lives, destruction of property and the environment. Establishing and maintaining slope stability using mechanical structures are costly. Hence, biotechnical slope protection offers an alternative which is not only cost effective but also aesthetically pleasing. A parametric study was carried out to discover the relationship between various eco-protection techniques, i.e., application of grasses, shrubs and trees with different soil properties as well as slope angles. Then the data have been used to develop a new hybrid ANFIS technique for prediction of factor of safety (FOS) of slopes. Four inputs were considered in relation to the different vegetation types, i.e., slope angle (θ), unit weight (γ), effective cohesion (c′), effective friction angle (ø′). Then, many hybrid ANFIS models were constructed, trained and tested using various parametric studies. Eventually, a hybrid ANFIS model with a high performance prediction and a low system error was developed and introduced for solving problem of slope stability. Keywords ANFIS · ANN fuzzy, eco-engineering · Factor of safety · Slope stability
* Meldi Suhatril [email protected] 1
Department of Civil Engineering, Faculty of Engineering, University of Malaya, 50603 Kuala Lumpur, Malaysia
2
Institute of Biological Sciences, Faculty of Science, University of Malaya, 50603 Kuala Lumpur, Malaysia
3
Civil Engineering Department, University of Hafr Al-Batin, Al-Jamiah, Hafr Al‑Batin, Eastern Province 39524, Kingdom of Saudi Arabia
4
5
Faculty of Civil Engineering, University of Tabriz, Tabriz, Iran DLSIIS, Universidad Politecnica de Madrid, Madrid, Spain
6
Centre for Biomedical Technology, Universidad Politécnica de Madrid, Madrid, Spain
7
Department of Computer Engineering, Neyshabur Branch, Islamic Azad University, Neyshabur, Iran
8
Department of Civil Engineering, Qeshm International Branch, Islamic Azad University, Qeshm, Iran
9
Research Center, Sulaimani Polytechnic University, Sulaimani 46001, Kurdistan Region, Iraq
10
Universidad UTE, Facultad de Ar
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