J4 ›› 2012, Vol. 50 ›› Issue (06): 1228-1232.

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Stock Abnormal Fluctuation Detection Algorithm Based onAdaptive Gaussian Process Machine Learning

DU Zhanwei1, YANG Wen2, YANG Yongjian1, XIAO Min1, BAI Yuan1   

  1. 1. College of Computer Science and Technology, Jilin University, Changchun 130012, China;2. Changchun Automobile Industry Institute, Changchun 130013, China
  • Received:2012-05-16 Online:2012-11-26 Published:2012-11-26
  • Contact: YANG Yongjian E-mail:yyj@jlu.edu.cn

Abstract:

On the basis of the analysis of historical data on the stock sample, we proposed an algorithm for the prediction of stock data to find the abnormal data to detect the abnormal data, with the introduction of Gaussian process machine learning method. The adaptive mechanism for the parameters of the Gaussian process was also solved with ant colony algorithm. Finally, some experiments show that the proposed algorithm can improve the accuracy and enhance customers’ satisfaction.

Key words: baseline algorithm, Gaussian process, machine learning, ant colony algorithm

CLC Number: 

  • TP391