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A study on UCS of stabilized peat with natural filler: A computational estimation approach

Dehghanbanadaki, Ali and Khari, Mahdy and Arefnia, Ali and Ahmad, Kamarudin and Motamedi, Shervin (2019) A study on UCS of stabilized peat with natural filler: A computational estimation approach. KSCE Journal of Civil Engineering, 23 (4). pp. 1560-1572. ISSN 1226-7988

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Official URL: http://dx.doi.org/10.1007/s12205-019-0343-4


This study applied two feed-forward type computational methods to estimate the Unconfined Compression Strength (UCS) of stabilized peat soil with natural filler and cement. For this purpose, experimental data was obtained via testing of 271 samples at different natural filler and cement mixture dosages. The input parameters for the developed UCS (output) model were: 1) binder dosage, 2) coefficient of compressibility, 3) filler dosage, and 4) curing time. The model estimated the UCS through two types of feed-forward Artificial Neural Network (ANN) models that were trained with Particle Swarm Optimization (ANN-PSO) and Back Propagation (ANN-BP) learning algorithms. As a means to validate the precision of the model two performance indices i.e., coefficient of correlation (R 2 ) and Mean Square Error (MSE) were examined. Sensitivity analyses was also performed to investigate the influence of each input parameters and their contribution on estimating the output. Overall, the results showed that MSE (PSO) < MSE (BP) while R 2 (PSO) > R 2 (BP) ; suggesting that the ANN-PSO model better estimates the UCS compared to ANN-BP. In addition, on the account of sensitivity analysis, it is found that the binder and filler content were the two most influential factors whilst curing period was the least effective factor in predicting UCS.

Item Type:Article
Uncontrolled Keywords:computation, fibrous peat
Subjects:T Technology > TA Engineering (General). Civil engineering (General)
Divisions:Civil Engineering
ID Code:87715
Deposited By: Widya Wahid
Deposited On:30 Nov 2020 21:09
Last Modified:30 Nov 2020 21:09

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