摘要
针对热工过程中表现出的非线性、时变性、大迟延和大惯性等特点,在分析热工过程辨识实际需要的基础上,采用扩展最小资源分配网络,建立了热工过程的非线性在线网络模型.这种模型能较好地解决神经网络序列在线学习问题,其计算量小、计算精度较高.实例计算验证了这种建模方法的有效性和快速性,为热工过程非线性模型的建立提供了一种新的方法.
Aiming at thermal process characteristics of nonlinear, time variance, great delay and big inertia, based on the actual requirement of thermal process identification, an on-line nonlinear network model adopting extended minimal resource allocation network（EMRAN） was proposed. This model can solve the on-line study problem of neural network series, its calculation amount is little and precision is higher. The example calculation proves validity and speediness of the modeling method which provides a new approach to make nonlinear model of thermal process.
出处
《动力工程》
CSCD
北大核心
2009年第5期432-435,共4页
Power Engineering
