Full TGIF Record # 228088
Item 1 of 1
DOI:10.11275/turfgrass1972.35.95
Web URL(s):https://www.jstage.jst.go.jp/article/turfgrass1972/35/2/35_2_95/_pdf
    Last checked: 08/21/2013
    Requires: PDF Reader
Publication Type:
i
Refereed
Author(s):Sasaki, Hiroyuki; Matsuura, Shoji; Kohyama, Kazunori
Title:A method for estimating productivity of Zoysia japonica using neural network
Source:Journal of Japanese Society of Turfgrass Science. Vol. 35, No. 2, 2007, p. 95-98.
Publishing Information:Tokyo, Japan: Japanese Society of Turfgrass Science
# of Pages:4
Related Web URL:https://www.jstage.jst.go.jp/article/turfgrass1972/35/2/35_2_95/_article
    Last checked: 08/21/2013
    Notes: English abstract only
Abstract/Contents:"Two production models, one using a neural network and the other using a multiple regression analysis, were constructed based on data of monthly dry matter production under various climatic conditions for Zoysia japonica. These models were then evaluated for practical use by comparing conformity of estimated data with actual harvest data. Using 105 items of harvest data with Zoysia japonica for three years, these models were compared for the estimation accuracy each other. The results clearly showed that the neural network had a higher coefficient of correlation between estimated data and harvest one. Accordingly, the neural network model showed the better estimation for the productivity."
Language:Japanese
References:8
Note:English summary as abstract
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ASA/CSSA/SSSA Citation (Crop Science-Like - may be incomplete):
Sasaki, H., S. Matsuura, and K. Kohyama. 2007. A method for estimating productivity of Zoysia japonica using neural network. (In Japanese) Journal of Japanese Society of Turfgrass Science. 35(2):p. 95-98.
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DOI: 10.11275/turfgrass1972.35.95
Web URL(s):
https://www.jstage.jst.go.jp/article/turfgrass1972/35/2/35_2_95/_pdf
    Last checked: 08/21/2013
    Requires: PDF Reader
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