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The pattern of grey fuzzy forecasting with feedback

机译:带反馈的灰色模糊预测模式

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摘要

The study on forecasting method has an important meaning for both theory investigation and practical application. Based on the theories of grey system and fuzzy recognition, the pattern of multi-objective and multi-dimensional grey fuzzy forecasting with feedback is presented in this paper. At first, according to the given weights, the weighting integrated value of samples is computed. Secondly, the method of fuzzy recognition with single index is employed to calculate the fuzzy classification of the integrated value. According to the cause analysis, the fuzzy classification of the integrated value is used to compute the weights of indexes. In a similar fashion, by repeating the above processes, the weighting integrated value and fuzzy classification with given accuracy are obtained at the same time. At last, the correlation coefficient between the weighting integrated values and forecasting objects is calculated by the processes of the principle of maximal relativity, optimization of the weighting integrated value of samples, establishment of the fuzzy forecasting pattern, and checking of the model's precision. The model is applied to predict groundwater dynamic levels, and the mean forecast accuracy of test samples is 96.50%.
机译:预测方法的研究对于理论研究和实际应用都具有重要意义。基于灰色系统理论和模糊识别理论,提出了带反馈的多目标,多维灰色模糊预测模型。首先,根据给定的权重,计算样本的加权积分值。其次,采用单指标模糊识别的方法对积分值进行模糊分类。根据原因分析,使用积分值的模糊分类来计算指标的权重。以类似的方式,通过重复上述过程,可以同时获得具有给定精度的加权积分值和模糊分类。最后,通过最大相对性原理,样本加权积分值的优化,模糊预测模型的建立以及模型精度的检验,计算出加权积分值与预测对象之间的相关系数。该模型用于预测地下水动态水平,测试样品的平均预测准确性为96.50%。

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