介绍原油优选模型中的非线性递归模型和混合整数规划模型技术。
Multi-period mixed integer linear programming model and applications for crude selection;
本文给出了在混合噪声中非线性递归最小均方误差算法的性能分析。
This paper presents the performance analysis of recursive least square algorithm with error-saturation in mixture noise.
复杂意谓它就是那样，非线性意谓递归和更高数学法则，而动态意谓非常数及非周期。
Complex implies just that, nonlinear implies recursion and higher mathematical algorithms, and dynamic implies nonconstant and nonperiodic.
应用该模型对线性结构和非线性结构在变阻尼控制和外荷载激励下结构的响应进行了数值仿真，表明所提的动态递归神经网络可以达到较高的预测精度。
Simulations on linear and nonlinear structures demonstrate that RDRNN is very effective on predicting the response of a structure subject to semi-active control and external excitation.
该方法是基于最小相位滤波器的复倒谱系数和其群迟延函数以及其系统函数之间的关系，通过一个非线性的递归方程求解分母多项式的系数。
Based on the relationship between the group delay function and the cepstral coefficients, the denominator polynomial coefficients can be determined through a nonlinear recursive difference equation.
针对仿射非线性系统，提出了一种新型的基于动态递归模糊神经网络(DRFNN)的间接自适应控制器。
A novel indirect adaptive controller based on dynamic recurrent fuzzy neural network (DRFNN) is proposed for affine nonlinear system.
本文用递归神经网络逼近非线性ARMA模型预测电力短期负荷。
The recursive neural network based nonlinear approaching ARMA model is adopted for short-term power load prediction in this paper.
辨识结果表明，动态递归网络模型优于传统辨识模型，适于非线性、不确定结构的辨识。
Results of identification show that the Elman's recurrent model is superior to the traditional model. It is adaptive to the identification of the non linear and uncertain structure.
基于递归神经网络给出了仅含一个非线性环节的一类非线性系统的自适应控制方案。
A scheme of adaptive control based on recurrent neural network is presented for a class of nonlinear systems only with a nonlinear part.
被传送给其它节点的带宽分配因子是通过使用过渡缓冲区大小的递归非线性函数计算出来的。
The bandwidth distribution factor transmitted to other node is calculated by using recursion nonlinear function of transition buffer.
ESN(回声状态网络)是一种新型的递归神经网络，可有效处理非线性系统辨识以及混沌时间序列预测问题。
As a new type of recurrent neural network, echo state network (ESN) is applied to nonlinear system identification and chaotic time series prediction.
针对板带轧机液压agc系统在线故障诊断问题，建立了一种基于非线性自回归滑动平均模型NARMA的递归神经网络，通过AIC定阶法确定模型阶次。
For on-line fault diagnosis of hydraulic AGC system on strip rolling mill, a recursive neural network model based on NARMA was established. The model order is determined by AIC method.
针对板带轧机液压agc系统在线故障诊断问题，建立了一种基于非线性自回归滑动平均模型NARMA的递归神经网络，通过AIC定阶法确定模型阶次。
For on-line fault diagnosis of hydraulic AGC system on strip rolling mill, a recursive neural network model based on NARMA was established. The model order is determined by AIC method.
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