Local decision making and decision fusion in hierarchical levels

被引:0
|
作者
Ulaş Beldek
Kemal Leblebicioğlu
机构
[1] Çankaya University,Electronic and Communication Engineering Department
[2] Middle East Technical University,Electrical and Electronics Engineering Department
来源
TOP | 2009年 / 17卷
关键词
Decision-making; Decision-fusion; Neural networks; Classification; Machine learning; 68T01; 68T05; 68T30; 68T37; 68T40;
D O I
暂无
中图分类号
学科分类号
摘要
Hierarchical problem solving is preferred when the problem is overwhelmingly complicated. In such a case, the problem should better be analyzed in hierarchical levels. At each level, some temporary solutions are obtained; then a suitable decision fusion technique is used to merge the temporary solutions for the next level. The hierarchical framework proposed in this study depends on reutilization or elimination of previous level local agents that together perform the decisions due to a decision-fusion technique: a performance criterion is set for local agents. The criterion checks the success of agents in their local regions. An agent satisfying this criterion is reutilized in the next level, whereas an agent not successful enough is removed from the agent pool in the next level. In place of a removed agent, a number of new local agents are developed. This framework is applied on a fault detection problem.
引用
收藏
页码:44 / 69
页数:25
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