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Volumn 20, Issue 4, 2011, Pages 463-473

Egg production forecasting: Determining efficient modeling approaches

Author keywords

Egg production modeling; Gompertz model; Neural network; Regression; Simulation

Indexed keywords


EID: 84856340867     PISSN: 10566171     EISSN: None     Source Type: Journal    
DOI: 10.3382/japr.2010-00266     Document Type: Article
Times cited : (23)

References (10)
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  • 2
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  • 3
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    • Alvarez, R.1    Hocking, P.M.2
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    • SAS Institute. 2004. SAS User's Guide: Statistics. Version 9.1 ed. SAS Inst. Inc., Cary, NC.
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  • 5
    • 84856322267 scopus 로고    scopus 로고
    • @Risk 4.0, Palisade Corporation, Ithaca, NY. Accessed Nov. 03, 2008
    • @Risk 4.0, Palisade Corporation, Ithaca, NY. Accessed Nov. 03, 2008. http://www.palisade.com/risk.
  • 6
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    • Ward Systems Group, Frederick, MD. Accessed Nov. 3, 2008
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  • 7
    • 33646920895 scopus 로고    scopus 로고
    • Comparison of forecasting methodologies using egg price as a test case
    • Ahmad, H. A., and M. Mariano. 2006. Comparison of forecasting methodologies using egg price as a test case. Poult. Sci. 85:798-807.
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    • Ahmad, H.A.1    Mariano, M.2
  • 8
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    • Poultry growth modeling using neural networks and simulated data
    • Ahmad, H. A. 2009. Poultry growth modeling using neural networks and simulated data. J. Appl. Poult. Res. 18:440-446.
    • (2009) J. Appl. Poult. Res , vol.18 , pp. 440-446
    • Ahmad, H.A.1
  • 10
    • 0023350668 scopus 로고
    • Comparison of three nonlinear regression models for describing broiler growth curves
    • Rogers, S. R., G. M. Pesti, and H. L. Marks. 1987. Comparison of three nonlinear regression models for describing broiler growth curves. Growth 51:229-239.
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    • Rogers, S.R.1    Pesti, G.M.2    Marks, H.L.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.