genetic programming (GP)
A Combined Genetic Programming for Microarray Data Analysis
... problems, Genetic Programming (GP)[1], which is a part of evolutionary computing, was proposed for this ...correlation. Genetic programming is based on natural selection and ...
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Testing the structure of a hydrological model using Genetic Programming
... Genetic Programming (GP) is a relatively new automatic programming technique for evolving computer programs to solve, or approximately solve, problems (Koza, ...
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Genetic programming and data structures
... Teller's primitives (if iteration or recursion are also included) extend GP so that the language used by evolving programs is Turing complete Teller, 1994c]. While in theory, any computable function can be evolved using ...
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On using surrogates with genetic programming
... One way to accelerate evolutionary algorithms with expensive fitness evaluations is to combine them with surrogate models. Surrogate models are efficiently computable ap- proximations of the fitness function, derived by ...
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A Genetic Programming PCA Hybrid Face Recognition Algorithm
... now, Genetic Programming (GP), acclaimed pattern recognition, data mining and relation discovery methodology, has been neglected in face recognition ...
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Genetic Programming Testing Model
... In genetic programming, genetic algorithm operates on a population of computer programs of varying size and shapes. The space of all possible computer programs is searched for the fittest individual ...
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An Analysis of the Impact of Functional Programming Techniques on Genetic Programming
... The Genetic Programming (GP) [Koza, 1989, 1990, 1992, 1994a] paradigm is a problem solving method based on a computational analogy to natural ...by genetic operations o f crossover and mutation to ...
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Genetic Programming Algorithm for Designing of Control Systems
... the genetic algorithm (GA) (used for numeric parameter tuning) and genetic programming (GP) (used for parameter tuning and structure selec- ...
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Recursion, lambda abstraction and genetic programming
... Module creation and reuse are essen- tial for Genetic Programming (GP) to be effective with larger and more complex problems. This paper presents a particu- lar kind of program structure to serve these ...
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PREDICTION OF ALGAL BLOOM USING GENETIC PROGRAMMING
... Conventionally, phytoplankton dynamics have been carried out using the process- based models by incorporating physical and biotic environmental variables in water quality model. This, however, is reported to suffer from ...
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Evolving text classification rules with genetic programming
... uses genetic programming (GP)(Koza 1992) to produce a synthesis of machine learning and knowledge engineering with the intention of incorporating advantageous attributes from ...
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Bedload transport predictions based on field measurement data by combination of artificial neural network and genetic programming
... 86 Malaysia, due to the difficulty of sampling and the possibility for wading in the water in these areas. New mathematical modelling methods were used to improve the sensitivity and performance of prediction equations ...
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A New Wave: A Dynamic Approach to Genetic Programming
... semantic genetic programming which operates by optimising the residual errors of a succession of short genetic programming runs, and then producing a cu- mulative ...short genetic ...
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Infilling of Rainfall Information Using Genetic Programming
... Genetic Programming (GP) is very similar Genetic Algorithm (GA), being an evolutionary algorithm based on Darwinian theories of natural selection and survival of the ...
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PolyGP: A Polymorphic Genetic Programming System in Haskell
... the Genetic Programming (GP) [Koza, 1992] paradigm, type information is one kind of heu- ristic knowledge that has been adopted to assist learning [Montana, 1995; Haynes, Wainwright, Sen and ...
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PolyGP: a polymorphic genetic programming system in Haskell
... Automatic programming relies on additional knowledge about the problem solution to guide code synthesis and transformation [Lenat, ...1984]. Genetic Programming (GP) [Koza, 1992] automatically ...
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Applying Genetic Programming to Bytecode and Assembly
... Traditional genetic programming (GP) is typically not used to perform unrestricted evolution on entire programs at the source code ...applying genetic programming to Java bytecode and x86 as- ...
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Genetic Programming based Face Recognition
... [9]. Genetic programming is an evolutionary computation technique that automatically solves problems without having to tell the computer explicitly how to do ...
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Meta genetic programming for static quantum circuits
... automatic programming system in the first ...linear genetic programming [7], which creates circuits of the form seen in the ...function, genetic mutation, and genetic crossover meth- ...
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Defining Locality in Genetic Programming to Predict Performance
... Abstract— A key indicator of problem difficulty in evo- lutionary computation problems is the landscape’s locality, that is whether the genotype-phenotype mapping preserves neighbourhood. In genetic ...
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