摘要
介绍了将人工神经元网络用于灾害性天气（暴雨）预报研究的情况。分析了天气预报问题的数学提法及困难所在，神经元网络用于天气预报的原理，暴雨预报的特点及我们对网络模型的改进。结果表明，神经网络确可通过学习从原始数据中提取足够的分类信息，达到较好的预报准确率，值得进一步研究。
The research on the application of artificial neural networks for calamitous (rainstorm) weather forecast is reported. The mathematical description of weather forecast,the difficult points of the problem,the principle of neural network for forecast,the characteristics of rainstorm forecast and our improvements of neural network models are described and analyzed. The results show that by learning from samples, the networks can extract enough classified imformations from original data and reach good forecast index. It means further works in this direction are worth.
出处
《气象》
CSCD
北大核心
1994年第6期43-47,共5页
Meteorological Monthly
基金
非线性研究攀登项目
关键词
神经网络
天气预报
neural network
calamitous weather forecast
improvement
