Prediction of strength enhancement of subgrade soil reinforced with geotextile using artificial neural network and M5P model tree

Singh, Tanvi; Goyal, Yash; Kumar, Suresh

Abstract

Geosynthetics layers are being implemented as reinforcement to enhance the strength of subgrade soil (which is calculated in terms of CBR). Present research work, aims at investigating the strength enhancement in terms of CBR through experimental study. Experiments were conducted on subgrade soil reinforcing it with single and double layer woven and non-woven geotextile layer were placed at depth M/3, M/2 and 2/3M from the top of CBR specimen, where Mis height of CBR specimen. Result indicate that woven geotextile offers more strength to subgrade soil than non-woven geotextile, further as depth of placement of reinforcement increases from top lesser is increase in strength for both the geotextile. Strength also increases when double layer was placed in comparison to single layer for both the geotextile. ANN and M5P was used to predict the CBR value, result suggest improved performance of ANN over M5P for present data.

Citation

Singh, T., Goyal, Y., & Kumar, S. (2020). Prediction of strength enhancement of subgrade soil reinforced with geotextile using artificial neural network and M5P model tree. European Journal of Molecular and Clinical Medicine, 7(8),

• Journal Article Type: Article
• Acceptance Date: Dec 9, 2020
• Online Publication Date: Dec 21, 2020
• Publication Date: Dec 21, 2020
• Deposit Date: Oct 6, 2022
• Publicly Available Date: Oct 6, 2022
• Journal: European Journal of Molecular & Clinical Medicine
• Electronic ISSN: 2515-8260
• Publisher: Ubiquity Press
• Peer Reviewed: Peer Reviewed
• Volume: 7
• Issue: 8
• Series ISSN: 2515-8260
• Item Discussed: geotechniques
• Keywords: Subgrade Soil, Geotextile, Geotextiles, Artificial Neural Network, Artificial Neural Network, M5P Model Tree, Geotechniques
• Public URL: https://uwe-repository.worktribe.com/output/10020570
• Publisher URL: https://ejmcm.com/article_4784.html