This paper introduces the time series AR (p) self-regression model. and how to apply it to predict the output of B. F. gas in Iron and Steel Works.
本文介绍了时间序列ar (P)自回归模型以及如何利用它来预测高炉煤气的产量。
The time series ar (p) self-regression model is widely applied to prediction in economic field. Most of researchers and technicians in engineering are not familiar with it.
时间序列ar (P)自回归模型多应用于经济预测领域，工程技术界多数人对此不太热悉。
For the frequently scene switching video traffic, it USES Markovian to simulate the switching among the scenes, and USES self-regression model to modeling inside the scene.
针对具有频繁场景切换的视频流，用马尔可夫链来模拟视频场景之间的切换，场景内部用自回归模型来建模。
The theory of linear regression and the theory of moving average are applied to analyse single data in time series, the model of a linear moving self regression forecast are given out.
应用线性回归分析和移动平均理论，对按时间次序排列的单一数据序列，给出了一种线性移动自回归预测模型，并对原始数据受不确定因素影响而产生的随机振荡，给出了合理的控制区间和运行通道。
Then it comes up with an arithmetic that will be used in regression testing according to the MRD model. This idea has been applied to the project "built-in self test for software…"
将以上研究思想应用于国家自然科学基金项目“软件可测性设计新概念—软件内建自测试”，实践证明，该模型有助于软件自动化测试的进一步研究。
Then it comes up with an arithmetic that will be used in regression testing according to the MRD model. This idea has been applied to the project "built-in self test for software…"
将以上研究思想应用于国家自然科学基金项目“软件可测性设计新概念—软件内建自测试”，实践证明，该模型有助于软件自动化测试的进一步研究。
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