摘要
应用神经网络中的径向基函数(RBF算法)及支持向量机算法(SVM算法),分别对某电厂再热器左右两侧汽温进行建模,并对结果进行分析。结果表明:两种人工智能技术都有快速建模的特点,但在精度上,RBF算法比只靠交叉验证进行参数寻优的SVM算法更精确。
Reheat steam temperatures on both sides of the reheater in a power plant were modeled using the radial basis function （RBF） in neural networks and the algorithm of support vector machine （SVM）, after which the calculation results were analyzed. Results show that both the artificial intelligence technologies have the features of rapid modeling and high precision. However, in terms of accuracy, RBF algorithm is superior to SVM algorithm, because SVM algorithm only relies on cross validation in optimization of parameters.
出处
《发电设备》
2015年第4期252-255,共4页
Power Equipment
关键词
人工智能技术
再热汽温
建模
artificial intelligence technology
reheat steam temperature
modeling
作者简介
唐志炳（1992-），男，在读硕士研究生，研究方向为热工自动化。E—mail：tangzbseu@163．com
