沙尘暴综合预报系统中场特征提取方法的研究

沙尘暴天气频繁发生,严重干扰和影响着人们的正常生活,对社会经济和生活环境均造成一定程度的危害.根据沙尘暴天气的成因及特点,在分析现有特征提取方法弊病的前提下,提出了ANN沙尘暴综合预报系统场特征提取方法.首先进行距平运算数据预处理,获取沙尘暴成因物理场样本;然后利用论文方法进行场特征提取.在此基础上,借助综合预报思想构建并实现了遗传ANN沙尘暴预测系统.仿真结果表明,论文所研究的场特征提取方法在提高沙尘暴预报的准确率方面做出了较大的贡献.

A Field Feature Extraction Method of Sand-dust Storm Ensemble Forecast System Based on ANN

The sand - dust storm happened more and more frequently in resent years. It not only seriously affects the normal life of people, but also do certain harm to the social economy and the environment. According to the origin and characteristic of sand - dust storm weather, a method of field feature extraction of sand - dust storm ensemble forecast system on GA - neural network is proposed in this paper, which is based on the analysis of the shortcomings of existing feature extraction methods. Firstly, the origin physics field sample of the sand - dust storm can be acquired after the preprocessing of characteristic data. Then the field feature extraction is performed by the presented method. On this basis, the dust storm forecast system on GA - neural network is constructed and realized with the aid of the ensemble forecast theory. The emulational results show that the presented method obtains a better achievement in enhancing the veracity of the sand - dust storm forecast.