Paper Info
Title
Detecting Potential Design Weaknesses In Shade Through Network Feature Analysis
Abstract
This preliminary study presents a hybridization of two research fields evolutionary algorithms and complex networks. A network is created by the dynamic of an evolutionary algorithm, namely Success-History based Adaptive Differential Evolution (SHADE). Network feature, node degree centrality, is used afterward to detect potential design weaknesses of SHADE algorithm. This approach is experimentally tested on the CEC2015 benchmark set of test functions and future directions in the research are proposed.
Year
DOI
Venue
2017
10.1007/978-3-319-59650-1_56
HYBRID ARTIFICIAL INTELLIGENT SYSTEMS, HAIS 2017
Keywords
Field
DocType
Differential evolution, SHADE, Complex network, Centrality
Data mining,Evolutionary algorithm,Computer science,Centrality,Differential evolution,Complex network,Artificial intelligence,Pattern recognition (psychology),Machine learning
Conference
Volume
ISSN
Citations 
10334
0302-9743
0
PageRank 
References 
Authors
0.34
18
4
Name
Order
Citations
PageRank
Adam Viktorin12916.76
Michal Pluhacek221747.34
Roman Senkerik337574.92
Tomas Kadavy42020.97