A multi-objective anomaly abnormal detection method based on the infrared and optical image fusion

Author(s):  
Ning Chu ◽  
Lianrui Mu ◽  
Zhiyan Li ◽  
Jiarui Ling ◽  
Yao Zhong
2014 ◽  
Vol 571-572 ◽  
pp. 177-182 ◽  
Author(s):  
Lu Wang ◽  
Yong Quan Liang ◽  
Qi Jia Tian ◽  
Jie Yang ◽  
Chao Song ◽  
...  

Community detection in complex network has been an active research area in data mining and machine learning. This paper proposed a community detection method based on multi-objective evolutionary algorithm, named CDMOEA, which tries to find the Pareto front by maximize two objectives, community score and community fitness. Fast and Elitist Multi-objective Genetic Algorithm is used to attained a set of optimal solutions, and then use Modularity function to choose the best one from them. The locus based adjacency representation is used to realize genetic representation, which ensures the effective connections of the nodes in the network during the process of population Initialization and other genetic operator. Uniform crossover is introduced to ensure population’s diversity. We compared it with some popular community detection algorithms in computer generated network and real world networks. Experiment results show that it is more efficient in community detection.


2011 ◽  
Vol 128-129 ◽  
pp. 465-468
Author(s):  
Gui Ying Liu ◽  
Shi Ping Su

That the control objectives of active power filter are diversified is an import measure to improve application efficiency of active power filter. This paper puts forward a new referenced signal detection method based on generalized orthogonal transformation, and expatiates of the basic theory of generalized orthogonal transformation and detection principles and their realization methods of all kinds of referenced signals. Finally, simulative results are given. Theory analysis and simulative results show validity of the proposed detection method.


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