基于神经网络的水稻不同生育周期长势预测模型

Prediction model of different growth cycle growth patterns of rice based on neural network

水稻的生长发育是一个复杂的过程,其中土壤、气候等环境因子对水稻的最终产量影响巨大。虽然有研究提出了天气、土壤等环境因素对水稻产量影响的预测模型,但因缺乏对水稻各个生育周期的长势的定量描述,所以对水稻不同生育周期的长势预测还不够细致。文章在水稻各周期生长模型特性和高邮灌区的水稻种植历史数据的基础上,设计并训练出环境因素对水稻各生育生长趋势影响预测模型。实验结果证明了该方法的有效性及合理性,对预测水稻在不同周期长势情况有一定的参考价值。

The growth and development of rice is a complex process,in which environmental factors such as soil and climate have a great impact on the final yield of rice.Although some studies have proposed a prediction model for the effects of environmental factors such as weather and soil on rice yield,the lack of quantitative description of the growth cycle of rice has not been sufficiently detailed for the growth cycle of rice.Based on the characteristics of rice growth cycle and the rice planting historical data in Gaoyou irrigation district,this paper designs and trains a prediction model of the influence of environmental factors on the growth and growth trends of rice.The experimental results demonstrate the validity and rationality of the method,and have certain reference value for predicting the growth of rice in different periods.