基于历史数据的黄海浒苔爆发规模预测

依据黄海浒苔初始覆盖面积及最大覆盖面积的历史数据,选取温度、光强、降水3种对于浒苔生长扩散最重要的影响因子,本文提出并建立了基于BP神经网络确定转换系数R的浒苔覆盖面积预测模型,可在浒苔出现初期即实现对本年度浒苔最大覆盖面积的模拟预测,并通过历史数据进行验证。结果表明,所预测的浒苔最大爆发情况与真实情况相符,研究成果可为浒苔的应急准备工作争取更多的时间提供一定参考。

Prediction of the outbreak scale of Enteromorpha prolifera in the Yellow Sea based on historical data

According to the historical data of initial coverage area and the maximum coverage area of Enteromorpha prolifera in yellow Sea, we selected the precipitation, temperature, light intensity, the three most important influence factors for the growth and diffusion of Enteromorpha prolifera, proposed and established a modle which base on BP neural network to determine the conversion coefficient R to prediction Enteromorpha prolifera coverage. It can realize the simulation and prediction of the maximum coverage area of Enteromorpha prolifera in this year at the early stage. By using historical data to validate, the results showed that the prediction of Enteromorpha prolifera maximum outbreak scale was consistent with the real situation. The results of this study can provide some references for the emergency preparation of Enteromorpha prolifera for more time.