Comparing neural networks, linear and nonlinear regression techniques to model penetration resistance

Turkish Journal of Agriculture and Forestry

Volumn 32, Issue 5, 2008, Pages 425-433

  Bayat, Hossein ^a   Neyshabouri, Mohammad Reza ^a   Hajabbasi, Mohammad Ali ^b   Mahboubi, Ali Akbar ^c   Mosaddeghi, Mohammad Reza ^c  

^a UNIVERSITY OF TABRIZ   (Iran)

^b ISFAHAN UNIVERSITY OF TECHNOLOGY   (Iran)

^c BU ALI SINA UNIVERSITY   (Iran)

Author keywords

Artificial neural networks; Bulk density; Cone index; Regression models; Water content

Indexed keywords

DATA FLOW ANALYSIS; FORECASTING; LINEAR NETWORKS; LINEAR REGRESSION; NEURAL NETWORKS; SOIL MOISTURE; WATER CONTENT;

BULK DENSITY; CONE INDEX; CORRELATION COEFFICIENT; LINEAR REGRESSION MODELS; NONLINEAR REGRESSION MODELS; NONLINEAR REGRESSION TECHNIQUE; REGRESSION MODEL; ROOT MEAN SQUARE ERRORS;

MEAN SQUARE ERROR;

ARTIFICIAL NEURAL NETWORK; MODELING; REGRESSION ANALYSIS; SOIL MOISTURE; SOIL PROPERTY; WATER CONTENT;

EID: 53249103474     PISSN: 1300011X     EISSN: None     Source Type: Journal    
DOI: 10.3906/tar-0708-11     Document Type: Article

References (28)

1. Busscher, W.J. 1990. Adjustment of flat-tipped penetrometer resistance data to a common water content. Trans. ASAE. 33: 519-524.
2. da Silva, A.P. and B.D. Kay. 1997. Estimating the least limiting water range of soils from properties and management. Soil Sci. Soc. Am. J. 61: 877-883.
3. Dexter, A.R. and M.A. Zoebisch. 2002. Critical limits of soil properties and irreversible soil degradation. In: Encyclopedia of Soil Science (Ed. R. Lal), Marcel Dekker, New York. pp. 272-276.
4. Dexter, A.R. 2004a. Soil physical quality. Part I: Theory, effects of soil texture, density and organic matter, and effects on root growth. Geoderma. 120: 201-214.
5. Dexter, A.R. 2004b. Soil physical quality. Part II: Friability, tillage, tilth and hard-setting. Geoderma. 120: 215-226.
6. Dexter, A.R. 2004c. Soil physical quality. Part III: Unsaturated hydraulic conductivity and general conclusions about S-theory. Geoderma. 120: 227-239.
7. Dexter, A.R., E.A. Czyz and O.P. Gate. 2007. A method for prediction of soil penetration resistance. Soil Till. Res. 93: 412-419.
8. Faure, A.G. and J.D.V. da Mata. 1994. Penetration resistance value along compaction curves. J. Geotech. Eng. 120: 46-59.
9. Grunwald, S., B. Lowery, D.J. Rooney and K. McSweeney. 2001a. Profile cone penetrometer data used to distinguish between soil materials. Soil Till. Res. 62: 27-40.
10. Grunwald, S., D.J. Rooney, K. McSweeney and B. Lowery. 2001b. Development of pedotransfer functions for a profile cone penetrometer. Geoderma. 100: 25-47.
11. Henderson, C., A. Levett and D. Lisle. 1988. The effect of soil water content and bulk density on the compactability and soil penetration resistance of some Western Australian sandy soils. Aust. J. Soil Res. 26: 391-400.
12. Kurup, P.U., G.Z. Voyiadjis and M.T. Tumay. 1994. Calibration chamber studies of piezocone test in cohesive soils. J. Geotech. Eng. 120: 81-107.
13. Laboski, C.A.M., R.H. Dowdy, R.P. Allmaras and J.A. Lamb. 1998. Soil strength and water content influence on corn root distribution in sandy soil. Plant Soil. 203: 239-247.
14. Lapen, D.R., G.C. Topp, M.E. Edwards, E.G. Gregorich and W.E. Pen. 2004. Combination cone penetration resistance/water content instrumentation to evaluate cone penetration-water content relationships in tillage research. Soil Till. Res. 79: 51-62.
15. Merdun, H., Ö, Çinar, R. Meral and M. Apan. 2006. Comparison of artificial neural network and regression pedotransfer functions for prediction of soil water retention and saturated hydraulic conductivity. Soil Till. Res. 90: 108-116.
16. Mulqueen, J., J.V. Stafford and D.W. Tanner. 1977. Evaluation of pentrometers for measuring soil strength. J. Terramech. 14: 137-151.
17. Pachepsky, Y., D. Timlin and G. Varallyay. 1996. Artificial neural networks to estimate soil water retention from easily measurable data. Soil Sci. Soc. Am. J. 60: 727-733.
18. Pidgeon, J.D. and B.D. Soane. 1977. Effects of tillage and direct drilling on soil properties during the growing season in a long-term barley mono-culture system. J. Agric. Sci. 88: 431-442.
19. Puppala, A.J., Y.B. Acar and M.T. Tumay. 1995. Cone penetration in very weakly cemented sand. J. Geotech. Eng. 121: 589-600.
20. Taylor, H.M. and L.F. Ratliff. 1969. Root elongation rates of cotton and peanuts as a function of soil strength and soil water content. Soil Sci. 108: 113-119.
21. To, J. and B.D. Kay. 2005. Variation in penetrometer resistance with soil properties: the contributin of effective stress and implications for pedotransfer functions. Geoderma. 126: 261-276.
22. Topp, G.C., D.R. Lapen, M.J. Edwards and G.D. Young. 2003. Laboratory calibration, in-field validation and use of a soil penetrometer measuring cone resistance and water content Vadoze Zone J. 2: 633-641.
23. Upadhyaya, S.K., L.J. Kemble and N.E. Collins. 1982. Cone index prediction equations for Delaware soils. ASAE paper. 82: 1452-1456.
24. Vaz, C.M.P., H.B. Luis and J.W. Hopmans. 2001. Contribution of water content and bulk density to field soil penetration resistance as measured by a combined cone penetrometer-TDR probe. Soil Till. Res. 60: 35-42.
25. Vepraskas, M.J. 1984. Cone index of loamy sands as influenced by pore size distribution and effective stress. Soil Sci. Soc. Am. J. 48: 1220-1225.
26. Whalley, W.R., P.B. Leeds-Harrison, L.J. Clark and D.J.G. Gowing. 2005a. The use of effective stress to predict the penetrometer resistance of unsaturated soils. Soil Till. Res. 84: 18-27.
27. Whalley, W.R., J. To, B.D. Kay and A.P. Whitmore. 2007. Prediction of the penetrometer resistance of soils with models with few parameters. Geoderma. 137: 370-377.
28. Zhang, R., D.E. Myers and A.W.W. Warrick. 1992. Estimation of spatial distribution of soil chemicals using pseudo-cross-variograms. Soil Sci. Soc. Am. J. 56: 1444-1452.