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Using Data Mining with Time Series Data in Short-Term Stocks Prediction: A Literature Review 被引量:2
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作者 José Manuel Azevedo Rui Almeida Pedro Almeida 《International Journal of Intelligence Science》 2012年第4期176-180,共5页
Data Mining (DM) methods are being increasingly used in prediction with time series data, in addition to traditional statistical approaches. This paper presents a literature review of the use of DM with time series da... Data Mining (DM) methods are being increasingly used in prediction with time series data, in addition to traditional statistical approaches. This paper presents a literature review of the use of DM with time series data, focusing on shorttime stocks prediction. This is an area that has been attracting a great deal of attention from researchers in the field. The main contribution of this paper is to provide an outline of the use of DM with time series data, using mainly examples related with short-term stocks prediction. This is important to a better understanding of the field. Some of the main trends and open issues will also be introduced. 展开更多
关键词 DATA Mining Time Series FUNDAMENTAL DATA DATA Frequency Application DOMAIN short-term stocks prediction
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基于相空间重构理论与递归神经网络相结合的股票短期预测方法 被引量:5
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作者 马千里 郑启伦 +1 位作者 彭宏 钟谭卫 《计算机应用研究》 CSCD 北大核心 2007年第4期239-241,245,共4页
根据股票指数时间序列复杂的非线性特性,提出以相空间重构理论与递归神经网络相结合的股票短期预测新方法。以相空间重构理论确定最佳延迟时间和最小嵌入维数,以最佳延迟时间为间隔的最小嵌入维数作为递归神经网络的输入维数,并按预测... 根据股票指数时间序列复杂的非线性特性,提出以相空间重构理论与递归神经网络相结合的股票短期预测新方法。以相空间重构理论确定最佳延迟时间和最小嵌入维数,以最佳延迟时间为间隔的最小嵌入维数作为递归神经网络的输入维数,并按预测相点步进递归的生成训练数据进行短期预测,提高了预测精度和稳定性。该方法应用于沪市股票综合指数预测,其结果与传统的单纯用BP网络模型预测的结果相比较,精度大大提高,证明了该预测模型和方法在实际时间序列预测领域的有效性和实用性。 展开更多
关键词 股票短期预测 时间序列 相空间 神经网络
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