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EMO
2005
Springer
68views Optimization» more  EMO 2005»
16 years 1 months ago
Multi-objective Optimization of Problems with Epistemic Uncertainty
Abstract. Multi-objective evolutionary algorithms (MOEAs) have proven to be a powerful tool for global optimization purposes of deterministic problem functions. Yet, in many real-w...
Philipp Limbourg
GECCO
2005
Springer
121views Optimization» more  GECCO 2005»
16 years 1 months ago
New evolutionary techniques for test-program generation for complex microprocessor cores
Checking if microprocessor cores are fully functional at the end of the productive process has become a major issue. Traditional functional approaches are not sufficient when cons...
Ernesto Sánchez, Massimiliano Schillaci, Ma...
FPL
2004
Springer
114views Hardware» more  FPL 2004»
16 years 1 months ago
Artificial Neural Networks Processor - A Hardware Implementation Using a FPGA
Several implementations of Artificial Neural Networks have been reported in scientific papers. Nevertheless, these implementations do not allow the direct use of off-line trained n...
Pedro Ferreira, Pedro Ribeiro, Ana Antunes, Fernan...
GECCO
2009
Springer
113views Optimization» more  GECCO 2009»
16 years 10 days ago
Variable size population for dynamic optimization with genetic programming
A new model of Genetic Programming with variable size population is presented in this paper and applied to the reconstruction of target functions in dynamic environments (i.e. pro...
Leonardo Vanneschi, Giuseppe Cuccu
HAIS
2009
Springer
16 years 9 days ago
Hybrid Evolutionary Algorithm for Solving Global Optimization Problems
Differential Evolution (DE) is a novel evolutionary approach capable of handling non-differentiable, non-linear and multi-modal objective functions. DE has been consistently ranked...
Radha Thangaraj, Millie Pant, Ajith Abraham, Youak...