Open AccessJournal Article
Gene Expression Programming: A New Adaptive Algorithm for Solving Problems.
TL;DR: Gene expression programming, a genotype/phenotype genetic algorithm (linear and ramified), is presented here for the first time as a new technique for the creation of computer programs with high efficiency that greatly surpasses existing adaptive techniques.
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Abstract: Gene expression programming, a genotype/phenotype genetic algorithm (linear and ramified), is presented here for the first time as a new technique for the creation of computer programs. Gene expression programming uses character linear chromosomes composed of genes structurally organized in a head and a tail. The chromosomes function as a genome and are subjected to modification by means of mutation, transposition, root transposition, gene transposition, gene recombination, and oneand two-point recombination. The chromosomes encode expression trees which are the object of selection. The creation of these separate entities (genome and expression tree) with distinct functions allows the algorithm to perform with high efficiency that greatly surpasses existing adaptive techniques. The suite of problems chosen to illustrate the power and versatility of gene expression programming includes symbolic regression, sequence induction with and without constant creation, block stacking, cellular automata rules for the density-classification problem, and two problems of boolean concept learning: the 11-multiplexer and the GP rule problem.
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Citations
Rotation forest with GEP-induced expression trees
Joanna Jedrzejowicz,Piotr Jędrzejowicz +1 more
- 29 Jun 2011
TL;DR: Two techniques used in the field of the supervised machine learning, including rotation forest and gene expression programming, are integrated to build a rotation forest based classifier ensembles using independently induced expression trees.
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Automatic synthesis of practical passive filters using clonal selection principle-based gene expression programming
Zhaohui Gan,Zhenkun Yang,Gaobin Li,Min Jiang +3 more
- 21 Sep 2007
TL;DR: Experimental results show that this approach can generate passive RLC filters quickly and effectively, and both the circuit topology and component parameters can be evolved simultaneously.
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Seismic Response Prediction of Self-Centering, Concentrically-Braced Frames Using Genetic Programming
Amir H. Gandomi,David A. Roke +1 more
- 02 Apr 2014
TL;DR: In this paper, the mean and standard deviation of SC-CBF peak roof drift response under the design basis earthquake using the most effective mechanical and geometrical parameters were predicted.
Modeling the performance of upflow anaerobic filters treating paper-mill wastewater using gene-expression programming
TL;DR: In this paper, the predictive ability of gene-expression programming (GEP) in the estimation of methane yield (Ym) and effluent substrate (Se) produced by two anaerobic filters was investigated.
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References
Genetic algorithms in search, optimization and machine learning
David E. Goldberg
- 01 Jan 1989
TL;DR: This book brings together the computer techniques, mathematical tools, and research results that will enable both students and practitioners to apply genetic algorithms to problems in many fields.
58.6K
•Book
Genetic algorithms in search, optimization, and machine learning
David E. Goldberg
- 01 Sep 1988
TL;DR: In this article, the authors present the computer techniques, mathematical tools, and research results that will enable both students and practitioners to apply genetic algorithms to problems in many fields, including computer programming and mathematics.
•Book
Genetic Algorithms
David E. Goldberg,William Shakespeare +1 more
- 01 Jan 2002
TL;DR: The present work expresses the problem as a multi-objective optimization problem and a methodology has been proposed based on multi-objective genetic algo-rithm (MOGA) that exploits the effectiveness of MOGA for searching global optimal solutions in selecting an appropriate image enhancement operator.
17.1K
Adaptation in Natural and Artificial Systems: An Introductory Analysis with Applications to Biology, Control and Artificial Intelligence
John H. Holland
- 01 May 1992
TL;DR: Initially applying his concepts to simply defined artificial systems with limited numbers of parameters, Holland goes on to explore their use in the study of a wide range of complex, naturally occuring processes, concentrating on systems having multiple factors that interact in nonlinear ways.
16.6K
•Book
Genetic Programming: On the Programming of Computers by Means of Natural Selection
John R. Koza
- 01 Jan 1992
TL;DR: This book discusses the evolution of architecture, primitive functions, terminals, sufficiency, and closure, and the role of representation and the lens effect in genetic programming.
15K