This paper presents a new method based on Attribute Theory and Bernstein Basic Function fitting after thorough study of stock investment and prediction technology.
本文在深入分析股票投资理论和股价预测方法的基础上，提出了利用属性论方法和波恩斯坦基函数拟合技术的股市预测算法。
The result shows that the method used in this paper can objectively and quantitatively determine the vertical deformation intensity and may be useful in the study on earthquake prediction.
结果表明，所采用的分析方法比较客观、定量地反映了地壳垂直形变强度，对地震分析预报研究具有实用意义。
In this paper, the traditional echo state network (ESN) through the structure and learning mechanism of the study, on the echo state network prediction method of chaotic time series.
本文主要通过对传统回声状态网络(esn)的结构和学习机理的研究，探讨了回声状态网络对混沌时间序列的预测方法。
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