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GEPGemeinschaftswerk der Evangelischen Publizistik gGmbH
GEPGlobal Economic Prospects
GEPGrid Engine Portal
GEPGauteng Enterprise Propeller (South Africa)
GEPGrolier Electronic Publishing
GEPGood Ecological Potential (water quality)
GEPGood Engineering Practice
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GEPGeneral English Program (various locations)
GEPGlobal Entrepreneur Program (various locations)
GEPGirls' Education Project (UNICEF)
GEPGene Expression Programming
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GEPGel Electrophoresis (molecular biology)
GEPGraduate Entry Programme (UK)
GEPGuanine Nucleotide-Exchange Protein
GEPGroup on Environmental Performance (Organization for Economic Cooperation and Development)
GEPGifted Education Programme
GEPGastro Entero Pancreatic (tumors)
GEPGeneral Electric Plastics
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GEPGround Entry Point
GEPGeen Enkel Probleem (Dutch: No Problem)
GEPGlobal Excess Partners (New York, NY)
GEPGood Efficacy Practice
GEPGrassroots Empowerment Project (Wisconsin)
GEPGroupe d'Expertise Pluraliste (French: Pluralistic Expertise Group; uranium mining)
GEPGenesis Environmental Projects (Israel)
GEPGuided Explosive Projectile (Deus Ex game)
GEPGold Electroplate
GEPGood Epidemiology Practice
GEPGrant Engineering Products
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GEPGross Earned Premiums (insurance)
GEPGood Environmental Practice
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GEPGoddard Experiment Package (telescope)
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GEPGeneral Election Period (US Medicare)
GEPGeneric Plan
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GEPGrupo Especial Policial
References in periodicals archive ?
Sherwood, "High energy physics event selection with gene expression programming," Computer Physics Communications, vol.
Bolandi, "A new predictive model for compressive strength of HPC using gene expression programming," Advances in Engineering Software, vol.
Gene expression programming (GEP) was invented by Candida Ferreira in 2001 [1, 2], which is a new achievement of evolutionary algorithm.
To further improve the performance of the GEP, this paper proposes an improved gene expression programming based on niche technology of outbreeding fusion (OFN-GEP).
Standard gene expression programming (ST-GEP), which was firstly put forward by Candida Ferreira in 2001 [1, 2], could be defined as a nine-meta group: GEP = (C, E, [P.sub.0], M, [phi], [GAMMA], [PHI], [PI], T), where C is the coding means; E is the fitness function; [P.sub.0] is the initial population; M is the size of population; [phi] is the selection operator; [GAMMA] is the crossover operator; [PHI] is the point mutation operator; [PI] is the string mutation operator; T is the termination condition.
This paper puts forward an improved gene expression programming based on niche technology of outbreeding fusion (OFN-GEP), and verifies the effectiveness and competitiveness of the proposed algorithm about the function finding problems.
The main objective of this paper is to investigate the accuracy of soft computing techniques such as gene expression programming, adaptive neuro fuzzy inference system and artificial neural network methods for the prediction of hourly water temperature in a lake at different measured depths.
In the present study, the performance of some soft computing techniques, namely gene expression programming, adaptive neuro fuzzy inference system and artificial neural network to predict hourly water temperatures at different layers of the Yuan-Yang Lake in north-central Taiwan has been compared.
Gene expression programming, A new adaptive algorithm for solving problems.
Ferreira, "Gene expression programming: a new adaptive algorithm for solving problems," Complex Systems, vol.
Ferreira, Gene Expression Programming: Mathematical Modeling by an Artificial Intelligence, Springer, 2nd edition, 2006.
The present proposed model was developed with the aid of computer using Gene Expression Programming (GEP) software.