支持向量机是继神经网络后机器学习的热点研究技术，它主要应用于分类和回归问题中。
SVM is the hot issue accompanying artificial neural network in machine learning. It involves any practical problems such as classification and regression estimation.
它不仅有助于科学家对机器学习和神经计算的深入研究，还有助于普通工程技术人员利用神经网络技术来解决真实世界中的问题。
It is not only helpful for scientists to investigate machine learning and neural computing but also helpful for common engineers to solve real world problems using neural network techniques.
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.
针对机器人动力学模型的不确定性和负载扰动，提出了一种采用神经网络的机器人迭代学习控制方法。
Aiming at dynamic model uncertainties and load disturbances of robot manipulators, an iterative learning control scheme using neural networks is presented.
支持向量机和神经网络都是目前关于机器学习技术的研究热点。
Support vector machine (SVM) and the neural network are both currently hot subject in the area of machine learning technology.
本文用支持矢量学习机和神经网络两种机器学习方法建立选择性环氧化酶-2抑制剂的活性预测模型，以期为选择性环氧化酶-2抑制剂药物的合成提供先导化合物。
Machine learning methods, including Support Vector Machines and Artificial Neural Network, are applied to the development of the classification models for the selective COX-2 inhibitors in this paper.
这个领域 有很多术语，例如连接机制、并行分布处理、神经计算、自然智能系统、机器学习算法和人工神经网络。
The field goes by many names, such as connectionism, parallel distributed processing, neuro-computing, natural intelligent systems, machine learning algorithms, and artificial neural networks.
这个领域 有很多术语，例如连接机制、并行分布处理、神经计算、自然智能系统、机器学习算法和人工神经网络。
The field goes by many names, such as connectionism, parallel distributed processing, neuro-computing, natural intelligent systems, machine learning algorithms, and artificial neural networks.
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