Article Per Year (5 Year)
p-Index From 2021 - 2026
0.23
P-Index
This Author published in this journals
All Journal Civil Engineering Journal
Muhammad Usman Arshid
Assistant Professor Department of Civil Engineering, University of Engineering and Technology Taxila, Punjab 47050,
Civil Engineering, Building, Construction & Architecture

Published : 1 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 1 Documents
Search
Journal : Civil Engineering Journal

 1 
Knowledge Based Prediction of Standard Penetration Resistance of Soil Using Geotechnical Database Muhammad Usman Arshid
Civil Engineering Journal Vol 7 (2021): Special Issue "Innovative Strategies in Civil Engineering Grand Challenges"
Publisher : Salehan Institute of Higher Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28991/CEJ-SP2021-07-01

Abstract

The current study aimed at predicting standard penetration resistance (N) of soil using particle sizes and Atterberg's limits. The geotechnical database was created subsequent to the field and laboratory testing. The sample collection points were distributed in a mesh grid pattern to have uniform sampling consistency. Artificial Neural Networks (ANN) were trained on the database to build a knowledge-based understanding of the interrelation of the given soil parameters. To check the efficacy of the model, the validation was carried out by predicting standard penetration resistance (N) for another 30 samples which were not included in the training data (444 samples). The trained ANN model has been found to predict N values in close agreement with the N values measured in the field. The novelty of the research work is the standard penetration prediction employing basic physical properties of soil. This proves the efficacy of the proposed model for the target civil engineering application. Doi: 10.28991/CEJ-SP2021-07-01 Full Text: PDF
Co-Authors