Abstract
Weak electrical signals of the plant were tested by a touching test system of self-made double shields with platinum sensors. Tested data of electrical signals were denoised with the wavelet soft threshold. A novel autoregressive integrated moving average (ARIMA) model of weak electric signals of the chrysanthemum was constructed by the information fusion technology for the first time, that is, Xt =1.93731Xt-1 - 0.93731Xt-2 + εt + 0.19287εt–1 - 0.4173 Xt-2 - 0.17443 Xt-4 - 0.07764 Xt-5 - 0.06222 Xt-7. A fitting standard deviation was 1.814296. It has a well effect that the fitting variance and standard deviation of the model are the minimum. It is very importance that the plant electric signal with the data fusion is to understand self-adapting regulations on the growth relationship between the plant and environments. The forecast data can be used as preferences for the intelligent system based on the adaptive characters of plants.
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Wang, L., Li, Q. (2010). ARIMA Signals Processing of Information Fusion on the Chrysanthemum. In: Wang, F.L., Deng, H., Gao, Y., Lei, J. (eds) Artificial Intelligence and Computational Intelligence. AICI 2010. Lecture Notes in Computer Science(), vol 6319. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-16530-6_29
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DOI: https://doi.org/10.1007/978-3-642-16530-6_29
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