Wenbin Dai1, Lina Wang1,2,*, Binrui Wang1, Xiaohong Cui1, Xue Li1
Phyton-International Journal of Experimental Botany, Vol.91, No.10, pp. 2283-2296, 2022, DOI:10.32604/phyton.2022.021096
Abstract Temperature in agricultural production has a direct impact on the growth of crops. The emergence of greenhouses has improved the impact of the original unpredictable changes in temperature, but the temperature modeling of greenhouses is still the main direction at present. Neural network modeling relies on sufficient actual data
to model greenhouses, but there is a widening gap in the application of different neural networks. This paper
proposes a greenhouse temperature prediction model based on wavelet neural network with genetic algorithm
(GA-WNN). With the simple network structure and the nonlinear adaptability of the wavelet basis function,
wavelet neural network (WNN)… More >
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