Implement of Fuzzy Logic system using table lookup scheme by Java language to predict time series data

J. Kokeš, N. Nghien
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Abstract

Forecasting the future time series values from the past values plays important role in daily life. There are some techniques support for time series analysis such as statistics, Neural Network (NN), Fuzzy Logic (FL) and fusion NN and FL. However, there is lack of easy, free and visual tools for users to analysis time series data. In this paper we try to use Java program language to implement of Fuzzy Logic system using table lookup scheme to predict time series data. The results of our experiments show that our tool can give a high accuracy of prediction results. Since program is written in Java language so it can run across hardware and software platform and easily embed into website for user run through Internet.
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用Java语言实现模糊逻辑系统对时间序列数据的查找表预测
从过去的时间序列值预测未来的时间序列值在日常生活中有着重要的作用。目前已有统计学、神经网络(NN)、模糊逻辑(FL)以及融合神经网络和模糊逻辑等技术支持时间序列分析,但缺乏方便、免费和可视化的工具供用户分析时间序列数据。本文尝试使用Java程序语言实现模糊逻辑系统,该系统采用查找表的方式来预测时间序列数据。实验结果表明,该工具具有较高的预测精度。由于程序是用Java语言编写的,所以它可以跨硬件和软件平台运行,并且很容易嵌入到网站中,供用户通过互联网运行。
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