EconPapers    
Economics at your fingertips  
 

Development of neuro-fuzzy and neuro-bee predictive models for prediction of the safety factor of eco-protection slopes

Maryam Safa, Puteri Azura Sari, Mahdi Shariati, Meldi Suhatril, Nguyen Thoi Trung, Karzan Wakil and Majid Khorami

Physica A: Statistical Mechanics and its Applications, 2020, vol. 550, issue C

Abstract: This study is aimed to investigate the surface eco-protection techniques for cohesive soil slopes along the selected Guthrie Corridor Expressway (GCE) stretch by way of analyzing a new set of intelligence techniques namely neuro-bee, artificial neural network (ANN) and neuro-fuzzy. 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. To reach the aim of the current study, a field investigations and numerical studies were conducted and a suitable database was prepared and established. By preparing factor of safety (FOS) as a single output parameter and a combination of the most important parameters on that, the desired models have been designed based on training and test patterns. In order to evaluate and compare the prediction precision of the developed models, a series of statistical indices, such as root mean squared error (RMSE), determination coefficient (R-square) and variance account for (VAF) are calculated. Many intelligence models with the most effective parameters on the mentioned models were developed to predict FOS. Based on the simulation results and the measured indices, it was found that the proposed neuro-fuzzy model with the lowest system error and highest R-square performs better as compared to other proposed ANN and neuro-bee models. Therefore, the neuro-fuzzy can provide a new applicable model to effectively predict the FOS of the slopes due to the fact that it is able to combine the advantages of the ANN and fuzzy inference system to indicate a high prediction capacity in solving problem of slope stability.

Keywords: Neuro-bee; Neuro-fuzzy; ANN; Slope stability; Eco-engineering; Guthrie corridor expressway (GCE) (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (8)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S037843711932237X
Full text for ScienceDirect subscribers only. Journal offers the option of making the article available online on Science direct for a fee of $3,000

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:550:y:2020:i:c:s037843711932237x

DOI: 10.1016/j.physa.2019.124046

Access Statistics for this article

Physica A: Statistical Mechanics and its Applications is currently edited by K. A. Dawson, J. O. Indekeu, H.E. Stanley and C. Tsallis

More articles in Physica A: Statistical Mechanics and its Applications from Elsevier
Bibliographic data for series maintained by Catherine Liu ().

 
Page updated 2025-03-19
Handle: RePEc:eee:phsmap:v:550:y:2020:i:c:s037843711932237x