基于实用弱化缓冲算子的质量成本灰色 DGM 预测模型

目的运用施以弱化缓冲算子的灰色DGM模型进行质量成本的预测。方法利用积分函数去除区间型数据的不确定性,将其转化为信息无偏的实数。进而分析质量成本和相关指标间的关联程度,并引入二阶弱化缓冲算子对受干扰的成本时间序列进行处理,最后建立质量成本估算预测的灰色DGM模型。结果结合案例与常用的指数函数作比较,结果显示,灰色DGM模型对质量成本的模拟精度更高,模拟误差可由指数模型的1.689%下降至0.118%。结论此模型能有效改善预测精度,具有一定的科学性和合理性。

DGM Prediction Model of Quality Cost Based on Practical Weakening Buffer Operator

Objective To predict the quality cost with grey discrete model based on weakening buffer operator. Methods The integral function was used to remove the uncertainty of interval data, and transform it into an unbiased real number. By analyzing the correlation between quality cost and related factors and introducing the second-order weakening buffer operator to deal with the interference cost series, the discrete grey model was finally established to estimate the quality cost. Results Compared with cases and commonly used exponential function, the result showed that the simulation precision of DGM for quality cost was high. The simulation error might be reduced from 1.689% of exponential model to 0.118%. Conclusion This model can be used to effectively change the prediction accuracy. It has certain practicability and rationality.