Strength Prediction of Stabilized Loose Sands with Alkali-Activated Ggbfs Using Artificial Neural Networks Methods

Author:

Fathizadeh Mersad,Heshmati R. Ali Akbar,Mardpour Shahriar

Publisher

Elsevier BV

Reference61 articles.

1. Machine learning methods to map stabilizer effectiveness based on common soil properties;A Gajurel;Transportation Geotechnics,2021

2. Prediction of UCS and CBR of microsilica-lime stabilized sulfate silty sand using ANN and EPR models; application to the deep soil mixing;A Ghorbani;Soils and Foundations,2018

3. Experimental Study on Strength and Microstructure of Cemented Soil with Different Suctions;C Yu;Journal of Materials in Civil Engineering,2019

4. Evaluation of the impact of thermal performance on various building bricks and blocks: A review;D S Vijayan;Environ Technol Innov,2021

5. Role of industrial based precursors in the stabilization of weak soils with geopolymer -A review;D Parthiban;Case Studies in Construction Materials,2022

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