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本文研究了对时间序列进行分析的模糊学习系统。为了在时间序列分析中达到良好效果，该系统将专家知识与计算机学习过程相结合。学习过程在成功的预测中起着重要作用。专家知识用于建立初始系统。学习过程则用于改进系统的性能。
This paper studies fuzzy learning systems that analyze time series. In order to achieve good results in time series analysis, the system combines expert knowledge with the computer learning process. The learning process plays an important role in the prediction of success. Expert knowledge is used to build the initial system. The learning process is used to improve system performance.