Empirical modeling of the compaction curve of cohesive soils

Canadian Geotechnical Journal

Volumn 38, Issue 1, 2001, Pages 29-45

  Basheer, I A ^a  

^a CALIFORNIA DEPARTMENT OF TRANSPORTATION   (United States)

Author keywords

Cohesive soils; Compaction curve; Modeling; Neural networks; Regression

Indexed keywords

EID: 57249110443     PISSN: 00083674     EISSN: None     Source Type: Journal    
DOI: 10.1139/t00-068     Document Type: Article

References (46)

1. Selection of methodology for neural network modeling of constitutive hystereses behavior of soils
2. Artificial neural networks: Fundamentals, computation, design, and application
3. A neural network for soil compaction
4. Estimating optimum water content and maximum dry unit weight for compacted clays
5. Environmental factors in soil compaction
6. Water content - Density criteria for compacted soil liners
7. Calculation of standard proctor density and optimum moisture content from mechanical, analysis, shrinkage factors, and plasticity index
8. Stress-strain modeling of sands using artificial neural networks
9. New nested adaptive neural network (NANN) for constitutive modeling
10. Seismic liquefaction potential assessed by neural networks
11. Compacted fill
12. Compaction of sand-processed clay soil mixtures
13. Ohio's typical moisture-density curves
14. Correlation of maximum dry density and grain size
15. Resilient modulus of cohesive soils
16. Equation for complete compaction curve of fine-grained soils and its applications
17. Resilient modulus for fine-grained subgrade soils
18. Using indicative properties to predict the density-moisture relationship of soils
19. Resilient properties of laboratory compacted subgrade soils
20. Analysis of compaction characteristics of fine grained soils
21. Utilizing computational neural networks for evaluating the permeability of compacted clay liners
22. On the identification of compaction characteristics by neuronets
23. Compaction control criteria for clay hydraulic barriers
24. Triaxial compression behavior of sand and gravel using artificial neural networks (ANN)
25. Interrelationships of compaction and index properties
26. Correlation of compaction and classification test data
27. Learning internal representations by error propagation
28. Structure and strength characteristics of compacted clays
29. Modular neural networks for predicting settlements during tunneling
30. Testing an artificial neural network for predicting soil hydraulic conductivity
31. Prediction of pile capacity using neural networks
32. Computation of the optimum moisture content in the moisture-density relationship of soils
33. Soil compaction and permeability prediction models