【摘要】 为了提高降雨中长期预测精度,将小波分析和支持向量机回归方法引入水文序列预测领域,给出了两种方法的思路和特点。在此基础上,尝试建立了基于小波分析-支持向量机(WA-SVM)的降雨量序列预测模型。通过小波分解,将原始复杂的降雨序列分解到不同的高频和低频等层次,对每层得到的分解重构序列分别采用支持向量机回归方法进行预测,最后合成原始序列的预测值。将该模型应用于实际流域月降雨量预测,并与单独支持向量机回归方法预测结果进行比较,结果表明该方法预测精度有明显提高。更多还原

【Abstract】 To enhance the precision of medium-and-long term rainfall forecast,the methods of wavelet analysis and support vector machine were introduced into the fields of hydrology series forecasting.Moreover,the rainfall estimate model was built up based on wavelet analysis and support vector machine(WA-SVM).It decomposes the original complex rainfall series to different layers through wavelet analysis,forecasts each layer by means of SVM,and finally obtains the forecasting results of the original time series by composition.The model is applied to estimate the monthly rainfall series in the watershed,and compare with the results of support vector machine(SVM).The result indicates that the forecast accuracy is elevated obviously.更多还原