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灰模型
    Main research results as follows:1. The mechanism and algorithm of grey model are thoroughly analyzed.
    1.深入分析了常用的灰模型的建模机理和算法。
    3. Basing on the grey model, the grey prediction is used in the fire control system to complete the maneuvering target trajectory prediction.
    3.以灰模型为基础,将灰预测方法用在火控系统的机动目标跟踪预测问题上,并在matlab6.5环境下,利用仿真的手段检验其效果,分析其优缺点。
    Using the method derived from the grey forecasting theory, this paper establishes the grey model for predicting the originate time of strong shocks in Yunnan arid Sichuan provinces.
    本文应用灰色预测的理论方法建立了云南、四川强震发震时间的灰色预测模型,表明对于Ms≥6.5地震,两省统一组成大区域灰模型,其预测值与观测值拟合很好; 对于Ms≥6.0的地震,则分省建立灰色预测模型比大区域的模型精度更高,这说明不同强度地震受不同尺度范围的控制因素作用。
    The conclusion is that the progressing process of increasing period or decreasing period that belongs to the contraction curve of mus- culi skeleti can be exactly reflected by grey model of monotone curve, and dividing and combination of the series is an effective method that improves the procision of grey model built on non-monotone curve.
    残差检验表明该模型的精度优于全数据序列建立的灰模型,并得出结论:单调变化曲线的灰模型能很好地反映骨骼肌收缩曲线上升期和缓慢下降期的发展变化过程,序列的分段、联合是提高非单调变化曲线的灰模型精度的一种有效方法。
    In this paper it is proved that the system cloud grey model SCGM(1,1)a0 of a monotone decreasing (or increasing) convex (or concave) sequence is a monotone decreasing (or increasing) convex(or concave) function.
    本文证明了单调递减(或递增)凸(或凹)序列的系统云灰模型是单调速减(或进增)凸(或凹)函数,从而得出了SCGM(1,1)(ao)具有更广泛的适用性和更高建模精度的结论.
    A grey model {GM (l, n)} was established to relate chlorophyll-b concentration with four factors among the ten.
    本文建立叶绿素-b与这4个海水理化因子的灰模型{GM(l,n)},结果表明,相关因子与叶绿素-b的浓度变化有着较好的吻合。
    There are many uncertain factors for electricity consumption with the characteristic of obvious changing tendency. Grey prediction for electricity consumption is carried out by using Grey Model(GM) based on Grey Theory.
    根据社会存在用电量不确定因素较多,变化趋势较为明显的特点,基于灰系统理论建立灰模型(GreyModel,GM)对用电量进行灰预测;
 

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