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116
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GECCO
2006
Springer
186views Optimization» more  GECCO 2006»
15 years 7 months ago
Genetic programming for agricultural purposes
Nitrogen is one of the most important chemical intakes to ensure the healthy growth of agricultural crops. However, some environmental concerns emerge (soil and water pollution) w...
Clément Chion, Luis E. Da Costa, Jacques-An...
137
Voted
GECCO
2008
Springer
145views Optimization» more  GECCO 2008»
15 years 4 months ago
Memory with memory: soft assignment in genetic programming
Based in part on observations about the incremental nature of most state changes in biological systems, we introduce the idea of Memory with Memory in Genetic Programming (GP), wh...
Nicholas Freitag McPhee, Riccardo Poli
CEC
2009
IEEE
15 years 10 months ago
Gate-level optimization of polymorphic circuits using Cartesian Genetic Programming
— Polymorphic digital circuits contain ordinary and polymorphic gates. In the past, Cartesian Genetic Programming (CGP) has been applied to synthesize polymorphic circuits at the...
Zbysek Gajda, Lukás Sekanina
CEC
2007
IEEE
15 years 10 months ago
Success effort and other statistics for performance comparisons in genetic programming
— This paper looks at the statistics used to compare variations to the genetic programming method. Previous work in this area has been dominated by the use of mean best-of-run ...
Matthew Walker, Howard Edwards, Chris H. Messom
SMC
2007
IEEE
118views Control Systems» more  SMC 2007»
15 years 10 months ago
One-class learning with multi-objective genetic programming
One-class classification naturally only provides one class of exemplars on which to construct the classification model. In this work, multiobjective genetic programming (GP) all...
Robert Curry, Malcolm I. Heywood