1) count-based model
计数回归模型
2) statistic AR model
统计自回归模型
3) statistical regression model
统计回归模型
1.
The principal component analysis of factors of BP neural network model and statistical regression model has been carried out by an example; and the effects of factor correlativity on the two kinds of dam monitoring models are studied.
通过实例分别对BP神经网络模型和统计回归模型进行了建模因子的主成分分析,通过对相应原始模型的比较,研究了因子相关性对两种模型的影响,结果证明因子相关性对BP神经网络模型基本无影响,对统计回归模型影响较大。
2.
To make full use of BP neural network model and statistical regression model of dam, through illustrations a comparison between them is made in three aspects, i.
当需对大坝的监测数据作分解和解释时,则适宜采用统计回归模型。
3.
On the basis of principle of the classical threshold auto--regression model, we advanced anew statistical regression model and a relative building method via introducing the semi--polynomialtransformation.
根据经典门限自回归模型的基本思想，引人半截多项式变换，导出了一种新的统计回归模型，并提出了相应的一整套建模方案。
4) measurement and regre ssion model
计量回归模型
5) regression mathematics models
回归数学模型
1.
By some main technological parameters (consumption of adhesive,hot-pressing pressure) and some basic physical indexes (density,moisture content,thickness),regression mathematics models are obtained when the main physical and mechanical properties of particleboard are analyzed by the method of multi-variance linear regression in order to predict other physical and mechanical properties.
通过刨花板主要生产工艺参数(施胶量、热压压力)以及刨花板成品的一些易测的物理性能指标(厚度、含水率以及密度)与刨花板成品的主要物理力学性能指标(吸水厚度膨胀率、静曲强度、内结合强度)进行多元线性回归分析,建立相关的回归数学模型,以达到对其主要物理力学性能进行预测。
6) Exponential autoregressive model
指数自回归模型
1.
A Nonlinear Time Sery Model for Flood Forecast——exponential autoregressive model;
一类洪水预报的非线性时序模型——指数自回归模型
2.
On the complex decay of Tongjizi reservoir induced seismicity,an exponential autoregressive model is constructed and seismic activity tendency is predicted.
本文从铜街子水库诱发地震的基本地质条件着手，采用了水库综合影响系数、概率预测、信息量预测、模糊预测等方法对其最大诱震震级进行了评估，并针对铜街子水库诱发地震的复式衰减特性，建立了指数自回归模型，对诱发地震的活动趋势进行了预测。
3.
The identification of exponential autoregressive model (EAR modal)is discussed in this paper.
讨论了指数自回归模型的辨识问题，证明了该模型最小二乘估计的目标函数的非凸性，并给出了使该函数为凸的条件；最后给出了辨识该模型的算法及该算法的收效性，并以数值例子加以说明。
补充资料：计数
统计（数目）；计算：不可～ㄧ难以～。
说明：补充资料仅用于学习参考，请勿用于其它任何用途。
参考词条