惯性灰色模型及其应用性质研究

研究灰色预测模型建模的演化过程,可以更好地了解模型的本质特征和状态变化。惯性灰色模型主要研究灰色预测模型建模的演化过程,了解系统变化状态。本文根据数据的力学特性,利用矩阵分析方法研究惯性灰色模型的建模步骤,简化文献［1］中惯性模型的结构参数和分量参数形式,总结求解各种数据序列的力学变换式,获取各种惯性灰色模型的建模机理。最后通过实例研究系统状态的演变过程,将惯性灰色GM(1,1)模型应用到交通流状态的判定中,得到三相交通流与三种惯性灰色GM(1,1)模型的对应关系。利用三种惯性模型模拟效果来准确判断交通流的状态,揭示交通系统实时特性,为交通规划、控制和优化提供可靠的理论依据。

Research on Grey Inertial Model and Its Application Property

Studying the evolution process of grey prediction model modeling can better understand the essential characteristics and state changes of the model. Inertial grey model mainly studies the evolution process of grey prediction model modeling to understand the state of system change. In this paper, the mechanical properties of data and the matrix analysis method are used to study the modeling steps of the inertial grey model, simplify the structural parameters and component parameters of the inertial model in reference ［1］, summarize the mechanical transformation formulas for solving various data sequences, and obtain the modeling mechanism of various inertial grey models. Finally, the evolution process of system state is studied through examples, the inertial gray GM(1,1) model is applied to the determination of traffic flow state, and the corresponding relationship between three-phase traffic flow and three inertial gray GM(1,1) models is obtained. At the same time, the simulation results of the three inertial models are used to accurately judge the state of the traffic flow, reveal the real-time characteristics of the traffic system, and provide a reliable theoretical basis for traffic planning, control and optimization.