Chapter
Apr 26, 2012
Introduction to the Development of an Information Management System for Soil Mix Technology Using Artificial Neural Networks
Publication: Geo-Frontiers 2011: Advances in Geotechnical Engineering
Abstract
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.
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© 2011 American Society of Civil Engineers.
History
Published online: Apr 26, 2012
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ASCE Technical Topics:
- Artificial intelligence and machine learning
- Computer programming
- Computing in civil engineering
- Engineering fundamentals
- Foundation construction
- Foundations
- Geomechanics
- Geotechnical engineering
- Information management
- Information systems
- Neural networks
- Soil analysis
- Soil compression
- Soil dynamics
- Soil mechanics
- Soil mixing
- Soil properties
- Soil strength
- Systems engineering
- Systems management
Authors
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Department of Engineering, University of Cambridge, Trumpington Street, Cambridge, CB2 1PZ.E-mail: [email protected]
Department of Engineering, University of Cambridge, Trumpington Street, Cambridge, CB2 1PZ.E-mail: [email protected]
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