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基于改进遗传小波神经网络的雷暴预报方法
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基于改进遗传小波神经网络的雷暴预报方法
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Journal Article
基于改进遗传小波神经网络的雷暴预报方法
2015
Overview
P457.9; 为了进一步提高雷暴预报的准确率，在分析研究雷暴预报方法的基础上，提出了一种了基于改进遗传算法优化小波神经网络的雷暴预报方法（ IGA?WNN）。该方法利用聚类分析和牛顿迭代法对多种群遗传算法的收敛方向和精度进行改进，避免了种群同质化与局部最优问题，采用改进的遗传算法对小波神经网络的初始权值阈值进行了优化。选用南京地区2008—2009年6—8月的探空和闪电定位资料，使用灰关联法挖掘出关联程度较大的对流参数作预报因子，归一化处理后输入模型，采用独立样本进行预报检验。结果表明，与 BP 神经网络等方法相比，IGA?WNN预报准确率更高，具有更好的非线性处理能力和泛化性。
Publisher
南京信息工程大学 江苏省气象探测与信息处理重点实验室，南京，210044,南京信息工程大学 气象灾害预报预警与评估协同创新中心，南京，210044
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