丁佳, 魏勇. 求解近似非齐次指数序列模型参数的新算法[J]. 内江师范学院学报, 2018, (4): 48-52. DOI:10.13603/j.cnki.51-1621/z.2018.04.009
引用本文: 丁佳, 魏勇. 求解近似非齐次指数序列模型参数的新算法[J]. 内江师范学院学报, 2018, (4): 48-52.DOI:10.13603/j.cnki.51-1621/z.2018.04.009
DING Jia, WEI Yong. A New Algorithm for Solving the Parameters of Approximate Non Homogeneous Exponential Sequence Model[J]. Journal of Neijiang Normal University, 2018, (4): 48-52. DOI:10.13603/j.cnki.51-1621/z.2018.04.009
Citation: DING Jia, WEI Yong. A New Algorithm for Solving the Parameters of Approximate Non Homogeneous Exponential Sequence Model[J].Journal of Neijiang Normal University, 2018, (4): 48-52.DOI:10.13603/j.cnki.51-1621/z.2018.04.009

求解近似非齐次指数序列模型参数的新算法

A New Algorithm for Solving the Parameters of Approximate Non Homogeneous Exponential Sequence Model

  • 摘要:针对模型的适用范围是近似非齐次指数序列情况, 首先给出了近非齐次指数灰色预测模拟公式中发展系数的简易求解方法.在发展系数已定的情况下通过首尾两项已知值确定预测系数和平移常数, 直接估算发展系数的简易方法, 既可以与通过首尾项作初始条件确定预测系数和平移常数方法结合形成一个全新模型, 也可以于通过平均相对误差最小为目标来确定预测系数和平移常数方法得到改进的新模型.理论和实例验证结果表明:新模型都能一定程度上提高建模精度, 此方法对传统模型和优化后的新模型都有效.

    Abstract:
    In response to the application scope of the model being an approximate non-homogeneous exponential sequence, first, a simple method for solving the developmental quotient coefficient of inhomogeneous exponential Grey prediction formula is given.After the developmental quotient is determined, then the prediction coefficient and shift constant can be worked out based on the known value of the first and last item, thus the developmental quotient can thus be directly estimated.Such a method, can either be combined with the method of determining the predictive coefficient and translation constant through the use of the first and last item as the initial condition, thus to develop a brand new model, or be joined with the method of determining the predictive coefficient and translation constant by minimizing the relative error via averaging as the goal to achieve a new improved model.The theoretical and practical results show that the new model can improve the modeling accuracy to a certain extent.This method works well for both the traditional model and the new model.

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