基于区间灰数的离散Verhulst直接模型

Verhulst Direct Model of Discrete Based on Interval Grey Number

灰色预测模型既有的研究成果,主要是围绕“实数”为建模对象的经典灰色预测模型,而对于以区间灰数为预测对象的探讨相对比较缺乏.针对传统Verhulst模型建模对象仅局限于实数序列这一缺陷,对Verhulst模型进行了拓展.对此,文章分析了传统Verhulst模型不足,提出了离散Verhulst直接模型;然后,构建了基于核和信息域的离散Verhulst直接模型,使区间灰数信息无偏的转换成实数信息,同时有效避免了原有的根据“灰度不减公理”按照取大准则确定预测值得灰度或信息域的计算性误差.最后,通过实例分析表明提出的新模型的有效性和实用性.

Modeling objects of the classical grey model are around the real number sequences,while it is relatively lacking for interval grey number in existing research results of grey prediction model.Aiming at the modeling objects of traditional Verhulst model are only confined to real number sequences,an expanding study of Verhulst model is given.Firstly,the article analyzes the shortcomings of traditional Verhulst model,and proposes Verhulst direct model of.discrete;then,it constructs a Verhulst direct model of discrete based on kerne.ls and information field,and transforms the interval grey number information unbiased into a real information,while effectively avoids the calculation error of kernels and information field.The error is caused by the axiom of undecreased degree of greyness.Finally,the proposed model is confirmed to have validity and practicality in this paper.