基于多粒度模糊CBR的价格预测方法

2008 ISECS International Colloquium on Computing, Communication, Control, and Management Pub Date : 2008-08-03 DOI:10.1109/CCCM.2008.353

H. Yuan, J. Ju, Ying Chen, Ming Chen

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引用次数: 1

摘要

科学准确地预测产品价格波动的能力在当代市场经济的发展中起着至关重要的作用，因此这一领域的研究非常活跃。本文提出了一种基于多粒度时间和基于实例推理的预测方法，并对具有一定波动特征的实例进行模糊匹配。该方法已在水产养殖中应用，并以水产品价格为检验数据。实验结果表明，该方法在水产品价格预测中具有较高的可行性和准确性。

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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A Multi-granularity & Fuzzy CBR Based Method for Price Forecast

The ability to scientifically and accurately forecast product price fluctuations plays a crucial role in the development of the contemporary market economy and consequently results in vigorous research in the area. This paper presents a new forecast method using multi-granularity of time and case-based reasoning (CBR) with fuzzy matching of cases featuring certain fluctuations. The method has been applied in aquaculture with aquatic product prices as test data. Results of experiments have proved the method highly feasible and accurate in aquatic product price forecasts.

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来源期刊

2008 ISECS International Colloquium on Computing, Communication, Control, and Management

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