针对轴承故障检测问题，提出一种基于相关向量机(RVM)的故障检测方法。
A new bearing fault detection approach based on relevance vector machine (RVM) is presented.
摘要提出了一种新的自适应约简相关向量机回归算法来估计图像的光照色度以达到色彩一致性目的。
A new regression algorithm of an adaptive reduced relevance vector machine is proposed to estimate the illumination chromaticity of an image for the purpose of color constancy.
利用均匀设计安排试验方案，并通过流体动力学仿真完成训练样本采集。选定相关向量机作为优化设计的评估函数。
The computational fluid dynamics (CFD) analysis of air-flow generating duct were utilized for sampling scheme given by uniform design to collect the train dataset.
此外，针对相关向量机回归计算结果受核参数影响较大的问题，本文还提出一种基于微粒群算法的相关向量机核参数自适应优化方法。
In addition, an adaptive kernel relevance vector machine based on PSO is presented to deal with the problem that the regression performance of classical RVM is often influenced by kernel parameters.
一个支持向量机的支持向量数相关的VC维是怎样的？有一个公式，关于这两个量？
How is the VC dimension of a support-vector machine related to its number of support vectors? Is there a formula relating these two quantities?
研究基于支持向量机和粗糙集的相关反馈图像检索算法。
Relevance feedback algorithm based on support vector machine and rough set for image retrieval is approached.
同时本文将机器学习和相关反馈结合起来用于图像检索，在实验中使用了K -NN、BP神经网络和支持向量机分类器。
At the same time, we used relevance feedback and machine learning used in image retrieval. K-NN, BP neural network and support vector machine classifiers were used in experiments.
内核方法和支持向量机(SVMs)与高斯过程相关并应用于分类和回归问题。
Kernal methods and support Vector Machines (SVMs) are related to Gaussian processes and can also be used in classification and regression problems.
算法从位平面相关性的角度出发提取特征值，使用支持向量机作为分类器，对LSB匹配算法进行隐写分析。
From the perspective of bit plane correlation, this algorithm extracts features, USES support vector machine as a classifier to detect LSB matching.
为了使数字水印综合性能更好，根据图像邻域像素之间具有很强的相关性这一特点，提出了一种基于支持向量机的图像水印算法。
Considering the coherence among neighborhood pixels in an image, a kind of spatial domain watermarking scheme based on support vector machine is proposed.
本项目以统计学习理论为基础，深入研究了应用支持向量机方法解决机械智能诊断和状态预测的相关问题。
Based on statistical learning theory (SLT), the relevant problems of solving the machinery intelligent diagnosis and condition prediction are thoroughly researched in this project by means of SVM.
特别是基于支持向量机的相关反馈，由于具有良好的泛化能力，因而进一步提高了检索性能。
Especially, SVM based relevance feedback greatly improve the performance of retrieval system with its good generalization.
特别是基于支持向量机的相关反馈，由于具有良好的泛化能力，因而进一步提高了检索性能。
Especially, SVM based relevance feedback greatly improve the performance of retrieval system with its good generalization.
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