Analysis of Light and Light Quality Control of Greenhouse Strawberry Based on BP Neural Network
Abstract
With the demand for agricultural output value, there is an increasing demand for artificial intelligence in agriculture. In this paper, the red strawberry is taken as an example. The problem of the good yield value of strawberry cannot be accurately controlled in the greenhouse in the north. Combined with BP neural network, the neural network algorithm is optimized. The neural network is constructed by using tensor flow to substitute the data for one hundred trainings. The accuracy is obtained, and the structure obtained after simulation is effective. Through our improved control process, strawberry is optimally controlled in terms of illumination, photoperiod and light quality, so that strawberry can also achieve high yield and high quality in the north.
Keywords
Red strawberry, BP neural network, Control, Illumination, Light quality, Photoperiod
DOI
10.12783/dtcse/iteee2019/28734
10.12783/dtcse/iteee2019/28734
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