1) scaled robust loss function
定标鲁棒损失函数
1.
The algorithm uses the subtractive clustering(SC) method to select hidden node centers of RBF network,and the gradient descent method with the scaled robust loss function(SRLF) as the objective function to adjust hidden node widths and the connection weights of the network.
使用相减聚类(Subtractive Clustering,SC)法选择RBF网络隐结点的中心,以定标鲁棒损失函数(Scaled Robust Loss Function,SRLF)为目标函数,采用梯度下降法调整隐结点的宽度和网络权值,从而使RBF网络的学习过程不受离群点的影响,并且能够快速收敛。
2) robust loss function
鲁棒损失函数
1.
In order to increase the generalization ability of SVM(support vector machine),a robust loss function is given.
为了提高支持向量机的泛化能力,给出了一个鲁棒损失函数,利用它建立了鲁棒支持向量机,并利用对偶原理推导出其对偶优化问题的形式,在此基础上设计了局部梯度算法,在这种算法中每次迭代只改变两个优化变量的值。
2.
Aiming at the normal Gaussian distributional noise,greater breadth noise and oddity point noise of product sales series and combing a designed robust loss function with wavelet kernel function,we propose a new waveletν-support vector machine,named as robust waveletν-support vector machine (RWν-SVM).
针对产品销售时序具有正态高斯分布、幅值较大、奇异点等混合噪音,设计一种鲁棒损失函数,并采用小波核函数,由此得到一种新的小波ν-支持向量机,即鲁棒小波ν-支持向量机(Robust wavelet ν-support vector machine,RWν-SVM)。
3.
To inhibit the normal Gaussian distributional noise,greater amplitude noise and singular points of product sales series,a robust loss function was designed,and a new support vector machine was obtained,named robust ν-support vector machine(Rν-SVM).
产品销售时序通常具有正态高斯分布、幅值较大、奇异点等混合噪音,为此,设计了一种鲁棒损失函数,得到一种新的支持向量机,即鲁棒ν-支持向量机。
3) objective function robustness
目标函数鲁棒性
1.
The paper described the strategies for feasibility robustness and objective function robustness respectively subjected to both probabilistic and non-probabilistic uncertainties in detail and proposed hybrid probabilistic and non-probabilistic models for structural robust design.
讨论了同时存在概率不确定性量和非概率不确定性量时可行鲁棒性和目标函数鲁棒性的实现策略,提出了基于概率和非概率混合模型的结构鲁棒设计方法。
2.
The paper describes the strategies for constraint function robustness and objective function robustness respectively subject to probabilistic and non-probabilistic uncertainties and proposes an approach to robust design of structures with probabilistic and non-probabilistic uncertainties.
提出了在概率不确定性和非概率不确定性同时存在时的约束函数鲁棒性和目标函数鲁棒性的实现策略及结构鲁棒设计方法。
4) robust function
鲁棒函数
1.
It is independent of feature detection algorithms,using the scan line as the matching unit,using the robust function as the matching cost function and using the ordering constraint to detect and correct errors in each matching unit in the disparity map.
该方法独立于特征点的检测算法,先以扫描线作为匹配单元,然后以鲁棒函数为匹配代价函数,最后用顺序约束对每一匹配单元的视差图进行检测与校正。
2.
The control system is evidently improved by self-tuning control, robust function and dead-time tracking measures.
介绍ＡＬＣＥＭ钢液面控制系统的结构与调节原理，分析系统存在的问题，应用自校正控制技术及鲁棒函数与时滞跟踪措施对系统进行改进，取得良好的效果。
5) loss function
损失函数
1.
Mis-acceptance and mis-rejection in product examination and analysis of quality loss function;
测量检验中误收、误废和质量损失函数的分析
2.
Research on stochastic facility layout problem based on loss function;
基于损失函数的随机设施布局优化分析
3.
Multi-output support vector regression with piecewise loss function;
具有多分段损失函数的多输出支持向量机回归
6) Lost function
损失函数
1.
The sample size in random sampling can then be determined through forming the lost function.
在随机抽样的前提下,应首先定性地分析样本容量确定的影响因素,然后对精度和费用这两个可以量化的因素进行定量分析,并通过构建损失函数达到确定随机抽样样本容量之目的。
补充资料：损失函数
损失函数
loss function
损失函数〔卜.云州地阅;uoTep‘柯田叫.a] 统计判定问题中，对于试验的每一种可能结局表示试验者损失(成本)的非负函数.设X是在样本空间任，刃，p，)(口‘。)中取值的随机变盘;D={心是根据X的实现关于参数a可以作出的一切可能判决的空间.在决策函数理论中，定义在OxD上的任一非负函数L称为损失函数.当参数的真值为e时(e‘O)，损失函数L在任一点(a，d)任exD的值表示作出判决d(d〔D)所造成的损失.
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