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Volumn 78, Issue 7, 1999, Pages 983-991

Improving neural network prediction of amino acid levels in feed ingredients

Author keywords

Amino acid profile; Artificial neural networks

Indexed keywords

GLYCINE MAX; TRITICUM AESTIVUM; ZEA MAYS;

EID: 0033162180     PISSN: 00325791     EISSN: None     Source Type: Journal    
DOI: 10.1093/ps/78.7.983     Document Type: Article
Times cited : (14)

References (20)
  • 1
    • 0028788276 scopus 로고
    • Application of artificial neural networks to clinical medicine
    • Baxt, W.A.G., 1995. Application of artificial neural networks to clinical medicine. Lancet 346:1135-1138.
    • (1995) Lancet , vol.346 , pp. 1135-1138
    • Baxt, W.A.G.1
  • 2
    • 0013519197 scopus 로고
    • Avoiding the great propagation trap
    • July
    • Caudill, M., 1991. Avoiding the great propagation trap. AI Expert, July 6 (7):29-35.
    • (1991) AI Expert , vol.6 , Issue.7 , pp. 29-35
    • Caudill, M.1
  • 3
    • 0042075577 scopus 로고    scopus 로고
    • Artificial neural network prediction of amino acid levels in feed ingredients: Advanced optimization
    • Abstr.
    • Cravener, T. L., and W. B. Roush, 1998. Artificial neural network prediction of amino acid levels in feed ingredients: advanced optimization. Poultry Sci. 77:(Suppl. 1): 53. (Abstr.)
    • (1998) Poultry Sci. , vol.77 , Issue.1 SUPPL. , pp. 53
    • Cravener, T.L.1    Roush, W.B.2
  • 7
    • 0002094946 scopus 로고
    • Data preparation for a neural network
    • Lawrence, J., 1991. Data preparation for a neural network. AI Expert. 6(11)34-41.
    • (1991) AI Expert , vol.6 , Issue.11 , pp. 34-41
    • Lawrence, J.1
  • 8
    • 0003495215 scopus 로고
    • California Scientific Software Press, Nevada City, CA
    • Lawrence, J., 1993. Introduction to Neural Networks. California Scientific Software Press, Nevada City, CA.
    • (1993) Introduction to Neural Networks
    • Lawrence, J.1
  • 9
    • 0042576588 scopus 로고
    • Amino acids in feed ingredients and their predictability
    • Monsanto, St. Louis, MO
    • Monsanto, 1986a. Amino acids in feed ingredients and their predictability. Monsanto Nutrition Update. Vol. 4:2. Monsanto, St. Louis, MO.
    • (1986) Monsanto Nutrition Update , vol.4 , pp. 2
    • Monsanto1
  • 10
    • 0042576587 scopus 로고
    • Amino acids in feed ingredients and their predictability. Part II. Animal byproducts
    • Monsanto, St. Louis, MO
    • Monsanto, 1986b. Amino acids in feed ingredients and their predictability. Part II. Animal byproducts. Monsanto Nutrition Update. Vol. 4:3. Monsanto, St. Louis, MO.
    • (1986) Monsanto Nutrition Update , vol.4 , pp. 3
    • Monsanto1
  • 11
    • 0043077324 scopus 로고
    • Amino acids in feed ingredients and their predictability. Part III. Grain based ingredients
    • Monsanto, St. Louis, MO
    • Monsanto, 1986c. Amino acids in feed ingredients and their predictability. Part III. Grain based ingredients. Monsanto Nutrition Update. Vol. 4:4. Monsanto, St. Louis, MO.
    • (1986) Monsanto Nutrition Update , vol.4 , pp. 4
    • Monsanto1
  • 13
    • 0004018909 scopus 로고
    • 9th rev. ed. National Academy Press, Washington, DC
    • National Research Council, 1994. Nutrient Requirements for Poultry. 9th rev. ed. National Academy Press, Washington, DC.
    • (1994) Nutrient Requirements for Poultry
  • 14
    • 0031134550 scopus 로고    scopus 로고
    • Artificial neural network prediction of amino acid levels in feed ingredients
    • Roush, W. B., and T. L. Cravener, 1997. Artificial neural network prediction of amino acid levels in feed ingredients. Poultry Sci. 76:721-727.
    • (1997) Poultry Sci. , vol.76 , pp. 721-727
    • Roush, W.B.1    Cravener, T.L.2
  • 15
    • 0030330925 scopus 로고    scopus 로고
    • Artificial neural network prediction of ascites in broilers
    • Roush, W. B., Y. Kochera Kirby, T. L. Cravener, and R. F. Wideman, Jr., 1996. Artificial neural network prediction of ascites in broilers. Poultry Sci. 75:1479-1487.
    • (1996) Poultry Sci. , vol.75 , pp. 1479-1487
    • Roush, W.B.1    Kirby, Y.K.2    Cravener, T.L.3    Wideman R.F., Jr.4
  • 16
    • 0031262807 scopus 로고    scopus 로고
    • Neural network prediction of ascites in broilers based on minimally invasive physiological factors
    • Roush, W. B., T. L. Cravener, Y. Kochera, Kirby, and R. F. Wideman, Jr., 1997. Neural network prediction of ascites in broilers based on minimally invasive physiological factors. Poultry Sci. 76:1513-1516.
    • (1997) Poultry Sci. , vol.76 , pp. 1513-1516
    • Roush, W.B.1    Cravener, T.L.2    Kirby, Y.K.3    Wideman R.F., Jr.4
  • 18
    • 0026254768 scopus 로고
    • A general regression neural network
    • Specht, D. F., 1991. A general regression neural network. IEEE Trans Neural Networks 2(6):568-576.
    • (1991) IEEE Trans Neural Networks , vol.2 , Issue.6 , pp. 568-576
    • Specht, D.F.1
  • 20
    • 0041574344 scopus 로고
    • Ward Systems Group, Inc., Frederick, MD
    • Ward Systems Group, 1993. NeuroShell 2® User's Manual. Ward Systems Group, Inc., Frederick, MD.
    • (1993) Neuroshell 2® User's Manual


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.