针对这一缺陷，将基于小样本理论的支持向量机学习方法应用到发动机的故障诊断中。
To solve the problem of lack of fault engine sample, support vector machines, which is a method based on small sample theory is applied.
用模糊综合评判方法与BAYES理论相结合，给出由小样本试验数据确定岩土参数的概率分布。
By combining BAYES theory with fuzzy comprehension evaluation method, this paper suggests a new method to determine the distribution of rock parameters.
支持向量机是一种基于统计理论的机器学习算法，在解决小样本、非线性及高维模式识别中有独特的优势。
Support vector machine is a kind of machine study algorithm based on statistic theory, it has special advantage in solving small sample, non-linear and high dimension mode recognition.
本文用模糊综合评判方法与贝叶斯理论相结合，给出由小样本实验数据来确定电子系统长储可靠性模型的方法。
In this paper, a method based on the fuzzy judgement and Bayesian theory to evaluate the model of storage reliability of radio fuse using simple sample data is presented.
对小样本且信息不完全的路面数据库建议采用灰色理论进行分析。
Gray theory is recommended for the evaluation of pavement condition when large samples and complete data are not available.
与传统统计学相比，统计学习理论是一种专门研究小样本情况下机器学习规律的理论。
Compared with statistical theory, statistical learning theory focuses on the machine learning of small sample size and can trade off between the complexity of models and generalization performance.
由于它有严格的数学理论支撑以及较强的泛化性能，它在解决小样本学习问题时尤其具有优势。
Because of its strict mathematical theory of support and good generalization performance, it addresses the problem of small sample study of particular advantage.
统计学习理论具有坚实的理论基础，为解决小样本学习问题提供了统一的框架。
Statistical Learning Theory is based on a solid theoretical foundation. It provides an unified framework for solving the small sample learning problem.
支持向量机是一种基于统计学习理论的机器学习算法，能够较好地解决小样本的学习问题。
As one algorithm of the machine learning based on the statistical learning theory, Support Vector machine (SVM) is specifically to the small samples learning case.
第二种为灰色系统理论方法，用此方法能解决实测地应力值小样本问题。
The second one is a method using gray system theory, with which problem of a few samples of measured in-situ stress value could be resolved.
支持向量机是数据挖掘的一项新技术，被认为是目前针对小样本的分类、回归等问题的最佳理论。
Support vector machine is a new technique of data mining, which is regarded as the best theory aimed at solving the problem of classification and regression of small sample pool at present.
建立在统计学习理论基础之上的支持向量机(SVM)，是一种基于结构风险最小的小样本机器学习方法。
Support vector machine (SVM) is a novel and powerful learning method which is derived based on statistical learning theory (SLT) and the structural risk minimization principle.
基于统计学习理论中结构风险最小化原则的支持向量机是易于小样本的机器学习方法。
Support vector machine (SVM) based on the structural risk minimization of statistical learning theory is a method of machine learning for small sample set.
并研究了正态分布的小样本容量的相容性检验问题的理论，提出了新的检验方法。
The article gives a research on the theory problem of Compatibility test on Normal Distribution with few samples. The new test method is put forward.
根据未确知数学理论，提出了小样本条件下灌注桩混凝土抗压强度代表值的未确知数分析法。
The unascertained mathematics was introduced to analyze the representative values of compressive strength of concrete core from cast in-suit pile at the condition of small sampling data.
针对航空产品工程计划中工序作业时间小样本输入条件的特征，提出了一种基于灰色系统理论的工序作业时间预测方法。
Aiming at the characteristics of small sampling in aeronautic-product project scheme, a new prediction method to acquire the time limit of working process was studied based on Grey System theory.
支持向量机（SVM）是建立在统计学习理论基础上的一种小样本机器学习方法，用于解决二分类问题。
Support Vector Machines(SVM) are developed from the theory of limited samples Statistical Learning Theory (SLT) by Vapnik et al. , which are originally designed for binary classification.
支持向量机(SVM)方法是基于统计学理论的一种新的机器学习方法，对解决小样本条件下的非线性问题非常有效。
The Support Vector machine (SVM) is a new machine learning method based on the statistical learning theory and it is very useful to solve nonlinear problems of short time series.
支持向量机(SVM)方法是基于统计学理论的一种新的机器学习方法，对解决小样本条件下的非线性问题非常有效。
The Support Vector machine (SVM) is a new machine learning method based on the statistical learning theory and it is very useful to solve nonlinear problems of short time series.
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