Financial trend forecasting with fuzzy chaotic oscillatory-based neural networks (CONN)

K. Kwong, Max H. Y. Wong, Raymond S. T. Lee, J. Liu, J. You
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引用次数: 2

Abstract

This paper describes a methodology for financial prediction by using an advanced paradigm from computational intelligence - Chaotic Oscillatory-based Neural Networks (CONN) and aid with fuzzy membership function. The method uses financial market data to predict market trends over a certain period of time. This approach may have a wide variety of applications but from financial forecasting perspective, it can be used to identify and forecast market patterns for providing valuable and useful advices to investors for making investment decisions.
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基于模糊混沌振荡神经网络(CONN)的金融趋势预测
本文介绍了一种基于混沌振荡神经网络(CONN)的金融预测方法,该方法是计算智能中的一种先进范式,并结合模糊隶属函数进行预测。该方法使用金融市场数据来预测一定时期内的市场趋势。这种方法可能有各种各样的应用,但从财务预测的角度来看,它可以用来识别和预测市场模式,为投资者的投资决策提供有价值和有用的建议。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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