人工智能技术在再热汽温建模中的应用  

Application of Artificial Intelligence Technology in Modeling of Reheat Steam Temperature

作　　者：唐志炳 王明春[1] 陶成飞 刘劲权 

机构地区：[1]东南大学能源与环境学院,南京210096

出　　处：《发电设备》2015年第4期252-255,共4页Power Equipment

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.

关 键 词：人工智能技术 再热汽温 建模 

分 类 号：TK223.73[动力工程及工程热物理—动力机械及工程]