一种新的在线最小二乘支持向量机算法在瓦斯预测中的研究

Xiao-hu Zhao, Ke-ke Zhao
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引用次数: 7

摘要

本文对时间序列预测进行了研究,针对传统最小二乘支持向量机在线学习的不足,提出了一种新的LS-SVM在线学习预测算法。将该算法应用于煤矿瓦斯预测中,并与实际数据和其他相关算法进行了比较,证明了该算法的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Study of a new online Least Squares Support Vector Machine algorithm in gas prediction
This paper studied on time series prediction, and proposes a new prediction algorithm of LS-SVM online learning against the shortcomings in the traditional online learning with least squares support vector machine. This algorithm was researched and used in coal mine gas prediction and had proved effective, compared with the actual data and other relative algorithms.
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