支持向量机是一种基于统计学习理论的新颖的机器学习方法，该方法已广泛用于解决分类和回归问题。
Support vector machines (SVM) are a kind of novel machine learning methods, based on statistical learning theory, which have been developed for solving classification and regression problems.
支持向量机是一种基于统计学习理论的新颖的机器学习方法，该方法已广泛用于解决分类和回归问题。
Support vector machines (SVM) are a kind of novel machine learning methods based on statistical learning theory, which has been developed to solve classification and regression problems.
特征权重学习是基于特征赋权的K近邻算法需要解决的重要问题之一，传统上提出了许多启发式的学习方法。
Feature weighting is one of the important problems for feature weighting based KNN algorithm, and many heuristic methods have been employed to solve the problem traditionally.
针对连续空间下的强化学习控制问题，提出了一种基于自组织模糊rbf网络的Q学习方法。
For reinforcement learning control in continuous Spaces, a Q-learning method based on a self-organizing fuzzy RBF (radial basis function) network is proposed.
针对编队问题的具体特性，提出了基于环境的记忆学习方法，使多机器人编队系统具有较强的环境自适应能力。
For the peculiarity of team formation, an environment-based learning method is proposed to enable the system of robot team formation to have stronger adaptability to the environment.
本文结合机器人路径规划问题介绍了增强式学习方法，实现了动态环境中基于增强式学习的自适应路径规划。
To solve the robots path planning problem in dynamic environment, this paper applies adaptive learning to path planning based on reinforcement learning.
讨论了基于案例的学习方法在月球探测器局部路径规划中的应用问题。
This paper presents a mobile robot part path planning scheme using case-based learning algorithm.
支持向量机是一种基于统计学习理论的机器学习方法，它解决了神经网络中存在的一系列问题。
Support Vector Machine(SVM) is a machine learning method based on Statistical Learning Theory. It can solve a series of issues of Neural Networks.
支持向量机是一种基于统计学习理论的机器学习方法，该理论主要研究在有限样本下的学习问题。
Support vector machine is a kind of machine learning algorithm based on statistical learning theory which mainly researches the learning of limited number of samples.
支持向量机(SVM)是基于统计学习理论的一种智能学习方法，可以用来解决样本空间的高度非线性的模式识别等问题。
Support Vector Machine (SVM) is an intellectual learning method based on the statistics theory. The SVM can solve problems of complicated nonlinear pattern recognition of spatial samples.
针对多标签主动学习速度较慢的问题，提出一种基于平均期望间隔的多标签分类的主动学习方法。
Aiming at the problems that active learning in multi-label classification is slowly, this paper proposes an improved method for multi-label classification which based on average expectation margin.
讨论了基于案例的学习方法在月球探测器局部路径规划中的应用问题。
This paper presents a mobile robot part path planning scheme using case-based learning algorithm. Case-based learning is relatively a new approach to path planning.
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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