Research on Prediction Model of Time Series Based on Fuzzy Theory and Genetic Algorithm

被引：2
作者：
Xiao-qin, Wu [1 ]
机构：
[1] Hefei Univ, Key Lab Network & Intelligent Informat Proc, Hefei 230601, Peoples R China
来源：
2012 INTERNATIONAL CONFERENCE ON MEDICAL PHYSICS AND BIOMEDICAL ENGINEERING (ICMPBE2012) | 2012年 / 33卷
关键词：
fuzzy theory; genetic algorithm; financial time series;
D O I：
10.1016/j.phpro.2012.05.205
中图分类号：
Q6 [生物物理学];
学科分类号：
071011 ;
摘要：
Fuzzy theory is one of the newly adduced self-adaptive strategies, which is applied to dynamically adjust the parameters o genetic algorithms for the purpose of enhancing the performance. In this paper, the financial time series analysis and forecasting as the main case study to the theory of soft computing technology framework that focuses on the fuzzy theory and genetic algorithms(FGA) as a method of integration. the financial time series forecasting model based on fuzzy theory and genetic algorithms was built. the ShangZheng index cards as an example. The experimental results show that FGA perform s much better than BP neural network not only in the precision but also in the searching speed. The hybrid algorithm has a strong feasibility and superiority. (C) 2012 Published by Elsevier B.V. Selection and/or peer review under responsibility of ICMPBE International Committee.
引用
收藏
页码：1241 / 1247
页数：7
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