A Self-Learning Method for Cognitive Engine Based on CBR and Simulated Annealing

2012 ◽  
Vol 457-458 ◽  
pp. 1586-1594
Author(s):  
Yi Jing Liu ◽  
Li Ya Chai ◽  
Jing Min Liu ◽  
Bo Wen Li
Keyword(s):  
Simulated Annealing ◽  
Learning Method ◽  
Cognitive Engine ◽  
Self Learning

A Self-Learning Method for Cognitive Engine Based on CBR and Simulated Annealing

2012 ◽  
Vol 457-458 ◽  
pp. 1586-1594 ◽  
Author(s):  
Yi Jing Liu ◽  
Li Ya Chai ◽  
Jing Min Liu ◽  
Bo Wen Li
Keyword(s):  
Simulated Annealing ◽  
Cognitive Radio ◽  
Communication Systems ◽  
Essential Difference ◽  
Learning Method ◽  
Cognitive Engine ◽  
Multi Objective ◽  
Environment Parameters ◽  
The Relationship ◽  
Self Learning

The essential difference of cognitive radio from traditional radio lies in its ability to sense, learn and adapt to the environment. Recently, the research for cognitive radio has focused on the configuration problems of multi-objective optimization. However, in actual communication systems, the observable environment parameters are limited. Besides, the relationship between the system’s inputs and outputs is often complicated. Thus, Cognitive radio (CR) needs to understand and adapt to the environment through learning. To solve the problem mentioned above, a self-learning method for Cognitive radio decision engine based on CBR and Simulated Annealing is proposed. The simulation results show that the proposed method has the advantages of self-learning, multi-objective adaptation and rapid convergence.

scholarly journals A self-learning method for improving the hot-rolled plate shape

2018 ◽  
Vol 452 ◽  
pp. 022024
Author(s):  
Chen Zhang ◽  
Ziying Liu ◽  
Changli Zhang ◽  
Xudong Li ◽  
Qiuna Wang
Keyword(s):  
Rolled Plate ◽  
Learning Method ◽  
Plate Shape ◽  
Hot Rolled ◽  
Self Learning
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