新型近似非齐次反向累加灰色模型研究及应用

Research on the Novel Approximate Non-homogeneous Grey Model with Opposite-direction Accumulated Generation and Its Application

为提高灰色预测模型对不同特征序列的适应性,避免模型参数估计与参数应用的“非同源性”,实现模型优化与模型检验两个准则的一致性,基于背景值、建模机理、初始条件三个视角构建了一种新型近似非齐次反向累加灰色模型.研究表明,该模型对衰减序列、增长序列、齐次指数序列和非齐次指数序列都有较高的精度,是对现有灰色预测模型的有效补充.

This research aims to improving the adaptability to different feature sequences,avoiding the“non-homology”between parameter estimation and parameter application of the model,and achieving the consistency between the two criteria of model optimization and model testing.The researchers constructed a novel approximate non-homogeneous grey forecasting model with opposite-direction accumulated generation based on background value,modeling mechanism and initial condition.The result shows that the novel model has high accuracy for decaying sequence,growing sequence,homogeneous and non-homogeneous exponential sequences,which is an effective supplement to the existing grey forecasting model.