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模型的阶的英文
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- 英文翻译
- 造句
- model order
- 模型 model; pattern
- 的 4次方是 The fourth power of 2 i ...
- 阶 steps; stairs
- 模型的 dummy; model; molded
- 仿真模型的 phantom
- 非模型的 non-modeled
- 模型的分类 category of model
- 模型的记法 model notation
- 模型的结构 structure of the model
- 模型的类型 types of models
- 模型的评价 model appraisal
- 模型的确定 model specification
- 模型的设定 specification of model
- 模型的修正 modifying the model
- 色觉的阶段模型 stage model of the color perception
- 模型的表示法 model notation
- 模型的存在性 the existence of models
- 模型的局限性 limitations of spice modeling spice
- 模型的流线谱 flow lines about model
- 模型的上半部 pattern cope
- 模型的完备性 completeness of a model
- 模型的网络层 network layer osi model osi; network layer，osi model osi
- 模型的运输层 transport layer osi model osi; transport layer，osi model osi
- 型号，样式，模型，典型的 mod model
- 值模型的价值 value of z scores
- The model has a higher order , which brings a lot of difficulties in our later work of vibration control
由于此模型的阶次太高，给以后的振动控制工作带来了极大的困难。 - This paper is based on the theory of differential equations of vehicle in six directions , a model of the vehicle to build . but the model is relatively complex , it is not easy to analyse . it needs to simplify
本文是以描述汽车六个方向运动的微分方程为基础，在matlab环境下建立汽车仿真模型，但是因为模型的阶次相对较高，使研究工作比较复杂，这就提出了简化模型的要求。 - Based on these models , the differential pressure fluctuation signals of gas - liquid two - phase flow under different flow regimes in various diameter pipelines are analyzed . experimental results show that the autoregressive orders of bubble flow and annular flow are bigger than that of slug flow
对不同管径不同流型下的差压波动信号进行了建模，在此基础上分析得出：弹状流流型下arma模型的阶数n最小，泡状流和环状流流型下的arma模型阶数n较大。 - And then the combined prediction model of the observed data is formed , which consider the correlation of the variable with the other variable and self - dependency of the variable itself fully . considering the affection of located random factors , an algorithm is worked over to determine the model ' s order number and parameters . when the condition changes , fitting degree of observed data and prediction accuracy of the model are enhanced through rolling optimization and modifying model parameters
考虑到现场的随机因素的影响，在对随机信号采用时间序列方法建立模型时，研究了一种确立模型的阶数和模型参数的算法；在工艺状况发生改变时，通过对模型的滚动优化，修正模型参数，提高模型对实时观测数据的拟合程度和预测的准确性，探索了一条观测数据序列建模的新途径。
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Last modified time:Thu, 14 Aug 2025 00:29:56 GMT
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