Results 221 to 230 of about 56,963 (262)

GENETIC REPRESENTATION AND GENETIC NEUTRALITY IN GENE EXPRESSION PROGRAMMING

Advances in Complex Systems, 2002
The neutral theory of molecular evolution states that the accumulation of neutral mutations in the genome is fundamental for evolution to occur. The genetic representation of gene expression programming, an artificial genotype/phenotype system, not only allows the existence of non-coding regions in the genome where neutral mutations can accumulate but
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Active Learning of Expressive Linkage Rules Using Genetic Programming

SSRN Electronic Journal, 2013
A central problem in the context of the Web of Linked Data as well as in data integration in general is to identify entities in different data sources that describe the same real-world object. Many existing methods for matching entities rely on explicit linkage rules, which specify the conditions which must hold true for two entities in order to be ...
Robert Isele, Christian Bizer
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Automatic generation of regular expressions from examples with genetic programming

Proceedings of the 14th annual conference companion on Genetic and evolutionary computation, 2012
We explore the practical feasibility of a system based on genetic programming (GP) for the automatic generation of regular expressions. The user describes the desired task by providing a set of labeled examples, in the form of text lines. The system uses these examples for driving the evolutionary search towards a regular expression suitable for the ...
BARTOLI, Alberto, DAVANZO, GIORGIO, DE LORENZO, ANDREA, MAURI, MARCO, MEDVET, Eric, SORIO, ENRICO   +5 more
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Expressive genetic programming

Proceedings of the 14th annual conference companion on Genetic and evolutionary computation, 2012
The language in which evolving programs are expressed can have significant impacts on the problem-solving capabilities of a genetic programming system. These impacts stem both from the absolute computational power of the languages that are used, as elucidated by formal language theory, and from the ease with which various computational structures can ...
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Genetic Neutrality in Naive Gene Expression Programming

2008 4th International Conference on Wireless Communications, Networking and Mobile Computing, 2008
Gene expression programming (GEP) is a genotype- phenotype system with non-coding regions in genome where possible neutral mutations would be accumulated. In this paper, a novel concept named naive gene expression programming (NGEP) is introduced. The main contributions include: (a) proposing a novel algorithm named NGEP, which decoding method based on
Ming-Fang Zhu, Chang-Jie Tang, Shao-Jie Qiao, Shu-Cheng Dai, Yu Chen   +4 more
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System Identification Using Genetic Programming and Gene Expression Programming

2005
This paper describes a computer program called ECSID that automates the process of system identification using Genetic Programming and Gene Expression Programming. ECSID uses a function set, and the observed data to determine an ODE whose behavior is similar to the observed data.
Juan J. Flores, Mario Graff
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Symbolic regression on noisy data with genetic and gene expression programming

Seventh International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (SYNASC'05), 2005
This paper presents a novel method to perform regression on a finite sample of noisy data. The purpose is to obtain a mathematical model for data which is both reliable and valid, yet the analytical expression is not restricted to any particular form.
Elena Bautu, Andrei Bautu, Henri Luchian
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Comparison of Genetic Programming, Grammatical Evolution and Gene Expression Programming Techniques

2014
The purpose of this paper is to compare the efficiency of three different evolutionary programming techniques – Genetic Programming, Grammatical Evolution and Gene Expression Programming. These algorithms were applied to different type test problems with the same set of parameters. The results of the experiments and some insights on similar experiments
Evaldas Guogis, Alfonsas Misevicius
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An Encoding Scheme for Generating λ-Expressions in Genetic Programming

2003
To apply genetic programming (GP) to evolve λ-expressions, we devised an encoding scheme that encodes λ-expressions into trees. This encoding has closure property, i.e., any combination of terminal and non-terminal symbols forms a valid λ-expression. We applied this encoding to a simple symbolic regression problem over Church numerals and the objective
Kazuto Tominaga, Tomoya Suzuki, Kazuhiro Oka   +2 more
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A Genetic Representation for Dynamic System Qualitative Models on Genetic Programming: A Gene Expression Programming Approach

2007
In this work we design a genetic representation and its genetic operators to encode individuals for evolving Dynamic System Models in a Qualitative Differential Equation form, for System Identification. The representation proposed, can be implemented in almost every programming language without the need of complex data structures, this representation ...
Ramiro Serrato Paniagua, Juan J. Flores, Carlos A. Coello Coello   +2 more
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