Title of article
Applied unsupervised learning in model reduction of linear dynamic systems
Author/Authors
Dragan D. Kukolj، نويسنده , , D. Popovic، نويسنده , , M. Borota، نويسنده ,
Issue Information
هفته نامه با شماره پیاپی سال 1997
Pages
9
From page
95
To page
103
Abstract
In this paper, a method of unsupervised learning is proposed for the purposes of reducing large-scale complex dynamic systems. Reduction of a system is carried out through the division of state variables into groups and through the selection of the characteristic representatives of each group. The proposed methodology is tested on an electric power system. The obtained results indicate that the model of the dynamic system can be significantly simplified while retaining its basic dynamic characteristics.
Keywords
Unsupervised learning , Self-organized neural network , Large-scale dynamic systems , Model reduction , Pattern recognition
Journal title
Computers and Mathematics with Applications
Serial Year
1997
Journal title
Computers and Mathematics with Applications
Record number
917975
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