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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 380-384A Bayesian Network Model for Aeration Management...

A Bayesian Network Model for Aeration Management of Stored Grain

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Abstract:

This paper discuses a Bayesian-network method for building an aeration management model for high performance management of stored grain. This model is designed and implemented with a dividing-layer architecture, which is used to complete aeration management of a number of stored grain warehouses in order to increase stored grain safety and to decrease stored grain management cost.

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Periodical:

Applied Mechanics and Materials (Volumes 380-384)

Pages:

4751-4756

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.380-384.4751

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Cite this paper

Online since:

August 2013

Authors:

Ling Sun, Ze Sheng Zhu

Keywords:

Aeration Management, Bayesian Network (BN), Management Architecture, Management Cost, Stored Grain Safety

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© 2013 Trans Tech Publications Ltd. All Rights Reserved

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[1] FAO. 2007, Global cereal grains production and post harvest losses. www. faostat. fao. org. Accessed 25 Nov (2011).

[2] Rajarammanna R, Jayas DS, White NDG. 2010, Comparison of deterioration of rye under two different storage regimes. J Stored Prod Res 46: 87–92.

DOI: 10.1016/j.jspr.2009.10.005

[3] Flinn PW, Hagstrum DW, Reed C, Phillips TW. 2009, Insect population dynamics in commercial grain elevators. J Stored Prod Res 46: 43–47.

DOI: 10.1016/j.jspr.2009.09.001

[4] Jian F, Jayas DS. 2012, Temperature monitoring. In Hagstrum DW, Phillips TW, Cuperus G (eds) Stored product protection. Kansas State University (in press).

[5] C. S. Chang and J. L. Steele, Development and evaluation of aeration control strategies for maintaining stored grain quality, Applied Engineering in Agriculture, vol 11, no. 4, pp.577-582, (1995).

DOI: 10.13031/2013.25780

[6] H. H. Converse, Grain aeration applications, ASAE paper, No. 87-119, St. Joseph, Mich.: ASAE, (1987).

[7] B. A. Mckenzie, L. V. Fossen, and H. J. Stockdale, Managing dry grain in storage, Pub. No. AED-20, Ames: Midwest Plan Service, Iowa State Univ., (1980).

[8] N. Qiu, J. E. Dixon, and J. L. Halderson, Experimental results of aeration control with feedback, ASAE Paper, No. 87-6545, St. Joseph, Mich.: ASAE, (1987).

[9] A. Ryniecki, D. S. Jayas, and W. E. Muir, A generalized control-strategy for near-ambient drying of wheat under canadian-prairie climate, Transactions of the ASAE, vol. 36, no. 4, pp.1175-1183, (1993).

DOI: 10.13031/2013.28448

[10] K. G. Murty, Linear Programming, New York: John Wiley & Sons, (1983).

[11] G. F. Cooper, A computer-based medical diagnostic aid that integrates causal and probabilistic knowledge, Ph, D. Thesis, Stanford, CA: Department of Information Sciences, Stanford University, (1984).

[12] H. Hogereen, et. al., Approaches to the building of Bayesian Belief Networks for Disease Diagnosis, Proc. of 7th Int. Symp. on Veterinary Epidemiology and Economics, Nairobi, August, 1994, pp.411-414.

[13] FAO, China: grain storage structures, Rome, Italy: Agriculture services bulletin No. 49, (1982).

[14] K. M. Butani and E. Singh, Decision support system for the selection of agricultural machinery with a case study in India, Computers and Electronics in Agriculture, vol. 10, no. 2, pp.91-104, (1994).

DOI: 10.1016/0168-1699(94)90014-0

[15] K. K. Khankari, R. V. Morey, and S. V. Patankar, Mathematical model for moisture diffusion in stored grain due to temperature gradients, Transactions of the ASAE, vol. 37, no. 5, pp.1591-1604, (1994).

DOI: 10.13031/2013.28246