DocumentCode
478011
Title
Analysis on Weak Electric Signals of Plants by the Autoregressive Model
Author
Wang, Lanzhou ; Wang, Miao ; Zhao, Jiayin
Author_Institution
Coll. of Metro logical Technol. & Eng., China Jiliang Univ., Hangzhou
Volume
1
fYear
2008
fDate
18-20 Oct. 2008
Firstpage
171
Lastpage
175
Abstract
Models of the autoregressive model of weak electric signals in two plants were set up for the first time: Crassula portulacea wais x (n) = 1.95516 x (n-1) - 0.91114 x (n-2) -0.41287 x (n-4) + 0.65251 x (n-5) - 0.12294 x (n-6) - 0.28019 x (n-7) - 0.19178 x (n-8) + 0.54703 x (n-9) - 0.12636 x (n-10) - 0.15383 x (n-11) + 0.21684 x (n-14) - 0.3721 x (n-15) + 0.37012 x (n-17) - 0.2541 x (n-19) + 0.15452 x (n-21) - 0.10477 x (n-23) + 0.03347 x (n-25). And Aloe vera var. chinensis was x (n) = 1.9591 x (n-1) - 1.4927 x (n-2) + .07205 x (n-3) - 0.80219 x (n-4) + 0.44582 x (n-5) - 0.30807 x (n-6) + 0.19658 x (n-7) - 0.34506 x (n-8) + 0.52419 x (n-9) - 0.339 x (n-10) + 0.16681 x (n-11) - 0.09664 x (n-12) + 0.03625 x (n-17) - 0.02005 x (n-18). The results of the AR model to forecast 10 values of the weak electric signals are well, and can be used as the preferences for the intelligent autocontrol system based on the adaptive characteristic of plants to achieve the energy saving on agricultural productions.
Keywords
autoregressive processes; forecasting theory; Crassula portulacea; adaptive characteristics; agricultural productions; autoregressive model; energy saving; forecasting theory; intelligent autocontrol system; weak electric signals; Automatic testing; Biological system modeling; Brain modeling; Educational institutions; Mathematical model; Plants (biology); Reactive power; Signal analysis; Signal processing; System testing; AR model; model fitting; plant; weak electric signal;
fLanguage
English
Publisher
ieee
Conference_Titel
Natural Computation, 2008. ICNC '08. Fourth International Conference on
Conference_Location
Jinan
Print_ISBN
978-0-7695-3304-9
Type
conf
DOI
10.1109/ICNC.2008.96
Filename
4666833
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