Optimization Algorithm for Plant Growth Factor Acquisition and Fusion Model Based on Dynamic Data-Driven
There are many kinds of plants on the earth, and the growth environments of plants are different. Agricultural data acquisition often fails to reflect the optimal environment for plant growth because of the long growth cycle and large differences in the growth environment. From data acquisition and fusion model optimization, this paper uses a dynamic data-driven method to obtain more accurate plant growth environment information. Firstly, an application framework of plant growth factors is proposed, under which an optimization algorithm of plant growth factors collection and fusion model driven is established by dynamic data. The analysis and simulation results show that the proposed optimization algorithm can be better used to collect and fuse plant growth factor data.