Implementation of Artificial Neural Network to Predict the Permeability and Solubility Models of Gypseous Soil
نویسندگان
چکیده
The objective of the present study is to make a database that describes leaching-permeability behavior collapsible gypseous soil. data will be implemented develop ANN prediction models for predicting saturated coefficient permeability and percentage solubility by weight. complex soil tedious time consume in testing have driven researchers use Artificial Neural Network (ANN) as tool prediction. objectives were investigate soils estimating soils. MATLAB R2015a software was used predict weight dataset this work included (513) records experimental measurements extracted from tests conducted on samples taken Baher Al-Najaf Iraq. Four input variables investigated most important influence According achieved statistical analysis, ANNs model reliable capability find out predictions with high-level accuracy. exhibited high rate dissolution soluble minerals content, which caused increase reach state long-term full saturation.
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ژورنال
عنوان ژورنال: pertanika journal of science and technology
سال: 2021
ISSN: ['0128-7680', '2231-8526']
DOI: https://doi.org/10.47836/pjst.29.1.06