为了提高对异常状态识别的适应性和有效性，提出了一种基于一类支持向量机的设备状态自适应报警方法。
To improve the adaptability and effectiveness of recognition on abnormal condition, a self-adaptive alarm method for equipment condition based on one-class support vector machine (OC-SVM) is proposed.
基于统计学习理论的支持向量机是一类新型的机器学习算法，由于它出色的学习性能，该技术已经成为当前学术界的研究热点。
The support vector machine based on statistical learning is a new type of machine learning algorithm, which has become the hot spot of academic study because of its excellent learning performance.
梯形模糊数样本是一类非随机样本，本文将讨论基于梯形模糊数样本的支持向量机。
The trapezoidal fuzzy number sample is one of non-real random samples. This dissertation will discuss the support vector machine base on trapezoidal fuzzy numbers.
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