趋势变化检测AIS

6th International Conference on Computer Information Systems and Industrial Management Applications (CISIM'07) Pub Date : 2007-06-28 DOI:10.1109/CISIM.2007.10

A. Domaradzki

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引用次数: 0

摘要

本文介绍了人工免疫系统在时间序列趋势变化检测中的新应用所取得的突出成果。作者的系统(GRASICA3)已在包含华沙证券交易所(WIG)主要指数每日配额的金融时间序列上进行了评估，此外还在使用蒙特卡洛方法生成的合成时间序列上进行了评估。与Gutjahr和Kingdon设计的参考书目中已知的其他系统的结果相比，已经获得了非常好的结果(趋势变化信号的准确度>60%)。在下一阶段，作者将GRASICA3结果与传统统计建模方法(如非常流行的Box-Jenkins和Arima X-12算法)的结果进行比较。

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AIS for Trend Change Detection

This article present outstanding results given by the new application of artificial immune systems in trend change detection in time series. Author's system (GRASICA3), has been evaluated on a financial time series containing daily quotas of the main index of the Warsaw's stock exchange (WIG) and additionally on a synthetic time series generated using the Monte Carlo method. Very good results which have been obtained (>60% of accuracy in trend change signals) are compared to results of other systems known from a bibliography, designed by Gutjahr and Kingdon. In the next stage the author provides a comparison of the GRASICA3 results to results given traditional statistical modeling methods such as, a very popular Box-Jenkins and Arima X-12 algorithms.

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6th International Conference on Computer Information Systems and Industrial Management Applications (CISIM'07)

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