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» Computational complexity and evolutionary computation
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177
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NCA
2006
IEEE
15 years 3 months ago
Evolutionary training of hardware realizable multilayer perceptrons
The use of multilayer perceptrons (MLP) with threshold functions (binary step function activations) greatly reduces the complexity of the hardware implementation of neural networks...
Vassilis P. Plagianakos, George D. Magoulas, Micha...
130
Voted
ISPASS
2008
IEEE
15 years 10 months ago
Independent Component Analysis and Evolutionary Algorithms for Building Representative Benchmark Subsets
— This work addresses the problem of building representative subsets of benchmarks from an original large set of benchmarks, using statistical analysis techniques. The subsets sh...
Vassilios N. Christopoulos, David J. Lilja, Paul R...
229
Voted
EC
2011
262views ECommerce» more  EC 2011»
14 years 10 months ago
Computer-Automated Evolution of an X-Band Antenna for NASA's Space Technology 5 Mission
Whereas the current practice of designing antennas by hand is severely limited because it is both time and labor intensive and requires a significant amount of domain knowledge, ...
Gregory Hornby, Jason D. Lohn, Derek S. Linden
140
Voted
IPPS
2007
IEEE
15 years 10 months ago
Time Series Forecasting by means of Evolutionary Algorithms
Many physical and artificial phenomena can be described by time series. The prediction of such phenomenon could be as complex as interesting. There are many time series forecasti...
Cristóbal Luque del Arco-Calderón, J...
148
Voted
GECCO
2008
Springer
186views Optimization» more  GECCO 2008»
15 years 4 months ago
A pareto following variation operator for fast-converging multiobjective evolutionary algorithms
One of the major difficulties when applying Multiobjective Evolutionary Algorithms (MOEA) to real world problems is the large number of objective function evaluations. Approximate...
A. K. M. Khaled Ahsan Talukder, Michael Kirley, Ra...