Shrestha, R and Al-Tabbaa, A (2011) Introduction to the development of an information management system for soil mix technology using artificial neural networks. Geotechnical Special Publication. pp. 816-825. ISSN 0895-0563Full text not available from this repository.
This paper introduces current work in collating data from different projects using soil mix technology and establishing trends using artificial neural networks (ANNs). Variation in unconfined compressive strength as a function of selected soil mix variables (e.g., initial soil water content and binder dosage) is observed through the data compiled from completed and on-going soil mixing projects around the world. The potential and feasibility of ANNs in developing predictive models, which take into account a large number of variables, is discussed. The main objective of the work is the management and effective utilization of salient variables and the development of predictive models useful for soil mix technology design. Based on the observed success in the predictions made, this paper suggests that neural network analysis for the prediction of properties of soil mix systems is feasible. © ASCE 2011.
|Divisions:||Div D > Geotechnical and Environmental|
|Depositing User:||Cron Job|
|Date Deposited:||18 May 2016 18:39|
|Last Modified:||29 Jul 2016 03:34|