2) generalization performance
泛化能力
1.
This paper presents an ensemble of support vector regression(ESVR) which has better generalization performance than other intelligent approaches.
泛化能力是智能方法用于参数预测的最重要的问题之一,提出了支持向量回归集成方法。
2.
The optimized BP artificial neural network model has advantageous properties such as more rapid calculation,high generalization performance and high accuracy.
经优化后的BP人工神经网络运算速度快、泛化能力强、预测精度高。
3.
This paper introduces the concepts and methods of the support vector machine(SVM),and points out that merging the invariance into the support vector machine by using VSV technique can improve the generalization performance of the SVM.
介绍了支持向量机(Support Vector Machine,SVM)的概念和方法,指出通过采用VSV(Virtual SV)方法将不变性常识(Invariance)融合于支持向量机,可提高模型的泛化能力。
3) generalization ability
泛化能力
1.
Research on enhanced generalization ability for the ANN’s identification model;
增强神经网络辨识模型泛化能力的研究
2.
Relevance Vector Machine Regression Models for Complex Surface Fitting and Its Generalization Ability
复杂曲面拟合的相关向量机模型及其泛化能力
3.
The field data are used to tests of network modeling and generalization ability.
针对高维非线性系统,分析了基于支持向量机网络的建模能力,并将增量回归支持向量机算法应用于锅炉燃烧过程建模,根据现场采集的数据进行支持向量机网络建模和泛化能力实验。
4) generalization performance
泛化性能
1.
A new algorithm for improving the generalization performance and real-time ability of feedforward neural networks;
提高前向神经网络泛化性能和实时性能的新算法
2.
Principal component analysis method to improve generalization performance of radial basis function network and its application research;
改善径向基函数网络泛化性能的主成分分析法及应用研究
3.
Support Vector Machine approach is considered a good candidate because of its good generalization performance,especially when the number of training samples is very small and the dimension of feature space is very high.
支持向量机方法被看作是对传统学习分类方法的一个好的替代,特别在小样本、高维情况下,具有较好的泛化性能。
5) generalization
[英][,dʒenrəlaɪ'zeɪʃn] [美]['dʒɛnrələ'zeʃən]
泛化能力
1.
Research on the generalization of radial basic function neural network and its application;
径向基函数网络泛化能力研究及其应用
2.
Improvement of Generalization of BP Network;
BP网络泛化能力的改进方法
3.
A New Approach for Improving Generalization Ability of MultiayerFeedfoward Networks;
提高前馈神经网络泛化能力的新算法
6) generalization capacity
泛化能力
1.
To counter the problem that the general BP algorithms and its improvements have weak generalization capacity,we study the Bayesian Regularization algorithm to enhance the neural network generalization capacity.
针对BP算法及其改进算法泛化能力不强的问题,探讨用贝叶斯正规化算法来提高网络泛化能力。
2.
Experiment result shows that ANN prediction model is characterized by better learning capacity and generalization capacity.
实验结果表明,神经网络预测模型具有较佳的学习能力和泛化能力。
3.
The hybrid algorithm improves the RBF neural network generalization capacity,and overcomes the shortcomings of the traditional TPO algorithm and the RBF neural networks.
仿真表明,该方法的收敛速度和预测精度优于传统径向基神经网络方法和粒子群—RBF神经网络方法及基于混沌理论的神经网络模型,该优化算法克服了径向基神经网络和传统的粒子群优化方法的缺点,改善了径向基神经网络的泛化能力,提高了贵州电网短期负荷预测的精度,各日预测负荷的平均百分比误差可控制在1。
补充资料：人脑的功能分化左右大脑半球的功能特化
李瑞端绘
[图]
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