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    金玲玲,汪刘一. 小波网络在深圳股市应用的研究[J]. 华南农业大学学报, 2003, 24(3): 82-84. DOI: 10.7671/j.issn.1001-411X.2003.03.022
    引用本文: 金玲玲,汪刘一. 小波网络在深圳股市应用的研究[J]. 华南农业大学学报, 2003, 24(3): 82-84. DOI: 10.7671/j.issn.1001-411X.2003.03.022
    shu
    Study on Applying of Wavelet Transform and Neural Networks in Shenzhen Stock Market[J]. Journal of South China Agricultural University, 2003, 24(3): 82-84. DOI: 10.7671/j.issn.1001-411X.2003.03.022
    Citation: Study on Applying of Wavelet Transform and Neural Networks in Shenzhen Stock Market[J]. Journal of South China Agricultural University, 2003, 24(3): 82-84. DOI: 10.7671/j.issn.1001-411X.2003.03.022
    shu

    小波网络在深圳股市应用的研究

    Study on Applying of Wavelet Transform and Neural Networks in Shenzhen Stock Market

      摘要
    • 摘要: 采用传统的人工神经网络模型对深圳证券成份指数进行模拟预测，在此基础上，进一步采用小波函数结合神经网络形成的小波网络对其进行拟合和预测，并对两种预测方法得到的结论误差进行分析、比较。结果显示，小波网络比单纯的神经网络模型预测精度高11．1595。

       

      Abstract: In the first approach, the conventional artificial neural networks(fuzzy perce ption) were used to approximate and predict the Shenzhen composite index. Based on this result, wavelet network were utilized, which is a hybrid of wavelet transform and neural network , to carry the same task. Comparing the prediction errors from both approaches clearly show that wavelet network offers very satisfied results.

       

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