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A comparative study on forecast analysis of growth-type time series with #x2018;Gap#x2019;

机译:“差距”生长型时间序列预测分析的比较研究

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Usually time series curve of the overall uptrend shows abnormal deviation phenomenon, called ‘gap’ phenomena. To solve the forecast problem for the time series data with ‘gap’, the output of aquatic products of Liaoning Province from 1985 to 2008 is analyzed as analysis object. The Logistic model, autoregressive moving average model and fuzzy time series model are used for the output of aquatic products of Liaoning Province analysis respectively. The comparative study of the forecast results and the error analysis results of the three kinds of models shows that proper fuzzy time series analysis methods are more effective for time series analysis. Two new time series data are formed through adjusting some data of the output of aquatic products of Liaoning Province. Each of them has two ‘gaps’ in the same side or in the opposite side. In this case the image analysis and error estimation still show that the fuzzy time series model has established good prediction effect.
机译:通常,整体上升趋势的时间序列曲线显示出异常的偏差现象,称为“差距”现象。为了解决与“差距”的时间序列数据的预测问题,辽宁省水产品产量从1985年到2008年被分析为分析对象。物流模型,自回归移动平均模型和模糊时间序列模型分别用于辽宁省水产品输出分析。预测结果的比较研究和三种模型的误差分析结果表明,适当的模糊时间序列分析方法对时间序列分析更有效。通过调整辽宁省水产品输出的一些数据来形成两个新的时间序列数据。它们中的每一个都有两个“差距”在同一侧或相对的一侧。在这种情况下,图像分析和误差估计仍然表明模糊时间序列模型已经建立了良好的预测效果。

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