Results 11 to 20 of about 174,883 (339)
Genetic programming as alternative for predicting development effort of individual software projects. [PDF]
PLoS ONE, 2012 Statistical and genetic programming techniques have been used to predict the software development effort of large software projects. In this paper, a genetic programming model was used for predicting the effort required in individually developed projects.
Arturo Chavoya +3 more
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A Genetic Programming Approach to Binary Classification Problem [PDF]
EAI Endorsed Transactions on Energy Web, 2021 The Binary classification is the most challenging problem in machine learning. One of the most promising technique to solvethis problem is by implementing genetic programming (GP).
Leo Santoso +4 more
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Solving even-parity problems using traceless genetic programming [PDF]
Congress on Evolutionary Computation, IEEE Press, Vol.2, pp.
1813-1819, 2004, 2021 A genetic programming (GP) variant called traceless genetic programming (TGP) is proposed in this paper. TGP is a hybrid method combining a technique for building individuals and a technique for representing individuals. The main difference between TGP and other GP techniques is that TGP does not explicitly store the evolved computer programs.
arxiv +1 more source
Scientific Reports, 2022 Niemann–Pick disease type C1 (NPC1) is a rare, prematurely fatal lysosomal storage disorder which exhibits highly variable severity and disease progression as well as a wide-ranging age of onset, from perinatal stages to adulthood. This heterogeneity has
Laura L. Baxter +8 more
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From Requirements to Source Code: Evolution of Behavioral Programs
Applied Sciences, 2022 Automatically generating executable code has a long history of arguably modest success, mostly limited to the generation of small programs of up to 200 lines of code, and genetic improvement of existing code. We present the use of genetic programming (GP)
Roy Poliansky +2 more
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Route Stability in the Uncertain Capacitated Arc Routing Problem
Frontiers in Energy Research, 2022 Power line inspections in a microgrid can be modeled as the uncertain capacitated arc routing problem, which is a classic combinatorial optimization problem.
Yuxin Liu +3 more
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The Effect of Multi-Generational Selection in Geometric Semantic Genetic Programming
Applied Sciences, 2022 Among the evolutionary methods, one that is quite prominent is genetic programming. In recent years, a variant called geometric semantic genetic programming (GSGP) was successfully applied to many real-world problems.
Mauro Castelli +4 more
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Ensemble Genetic Programming [PDF]
, 2020 Ensemble learning is a powerful paradigm that has been usedin the top state-of-the-art machine learning methods like Random Forestsand XGBoost. Inspired by the success of such methods, we have devel-oped a new Genetic Programming method called Ensemble GP. The evo-lutionary cycle of Ensemble GP follows the same steps as other GeneticProgramming systems,
Nuno M. Rodrigues +2 more
openaire +3 more sources
Forecasting and forecast-combining of quarterly earnings-per-share via genetic programming
Estudios de Administración, 2008 In this study we examine different methodologies to estimate earnings. More specifically, we evaluate the viability of Genetic Programming as both a forecasting model estimator and a forecast-combining methodology.
Arturo Rodríguez, Joaquín Trigueros
doaj +1 more source
Algorithms, 2021 Genetic Algorithms are stochastic optimization methods where solution candidates, complying to a specific problem representation, are evaluated according to a predefined fitness function.
Jalal Al-Afandi, András Horváth
doaj +1 more source