Indexed by:
Abstract:
应用RBF神经网络辨识方法建立了锅炉燃烧系统非线性模型,它可在运行中自动学习,适应很大工况范围及锅炉特性的时变性.应用结果表明所建立的模型能有效跟踪锅炉运行特性,具有很好的泛化能力,为锅炉燃烧系统优化控制和在线预测奠定了基础.
Keyword:
Reprint 's Address:
Email:
Version:
Source :
福州大学学报(自然科学版)
ISSN: 1000-2243
CN: 35-1337/N
Year: 2004
Issue: 3
Volume: 32
Page: 295-297,306
Cited Count:
SCOPUS Cited Count:
ESI Highly Cited Papers on the List: 0 Unfold All
WanFang Cited Count:
Chinese Cited Count:
30 Days PV: 2
Affiliated Colleges: