Results 251 to 260 of about 208,088 (288)

Gene expression programming with multiple chromosomes

International Journal of Modelling, Identification and Control, 2011
Gene expression programming (GEP) has been widely used in the areas of pattern recognition and knowledge discovery, however, when dealing with complicated problems, it is very time-consuming and the number of generations is large. In order to overcome these drawbacks, this paper proposes a multi-chromosomes GEP algorithm (MC-GEP).
Bo Wang, Min Yao, Rong Zhu
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Generating plants with gene expression programming

Proceedings of the 5th international conference on Computer graphics, virtual reality, visualisation and interaction in Africa, 2007
The simulated evolution of botanical trees and other plants is explored in this paper. We present a model to simplify the creation of plants by following the genotype/phenotype approach of Gene Expression Programming to generate L-Systems. Our model describes a specific organism (a plant) with a genotype that can be expressed as an L-System.
Johannes Venter, Alexandre Hardy
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Coordination of gene expression programs

2020
Most cellular processes depend on the activity and interactions of proteins. The proteome, i.e. the entire set of proteins in a specific condition, is shaped by regulation of transcription, mRNA-degradation, -processing, -storage, -translation and protein degradation.
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Gene expression programs in mammalian spermatogenesis

Development
ABSTRACT Mammalian spermatogenesis, probably the most complex of all cellular developmental processes, is an ideal model both for studying the specific mechanism of gametogenesis and for understanding the basic rules governing all developmental processes, as it entails both cell type-specific and housekeeping molecular processes ...
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Code Reuse in Gene Expression Programming

Applied Mechanics and Materials, 2011
Gene expression programming (GEP) is a kind of phenotype/genotype based evolutionary computation. Code reuse is an important issue in GEP. Various methods are used in current literature to achieve this task. In this paper, we compared six GEP based algorithms by experiments.
Qu Li, Min Yao, Wei Hong Wang, Yan Ye Du
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Gene Expression Programming with DAG Chromosome

2007
GEP(Gene Expression Programming) is applied to comprehensive fields such as Symbolic Regression, Parameter Optimization, Cellular Automate etc[2].With Kara-style chromosome, GEP can only express tree phynotype. This limits the expressiveness of the program that can be evolved.
Hui-yun Quan, Guangyi Yang
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Binary representation in gene expression programming

Proceedings of the 11th Annual conference on Genetic and evolutionary computation, 2009
One of the main problems that arises when using gene expression programming (GEP) conditions in learning classifier systems is the increasing number of symbols present as the problem size grows. When doing model-building LCS, this issue limits the scalability of such a technique, due to the cost required.
Jose G. Moreno-Torres, Xavier Llorà, David E. Goldberg   +2 more
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Probabilistically Guided Prefix Gene Expression Programming

2008
Over the years there has been an increasing interest in probabilistically oriented Evolutionary Algorithms (EAs), but it has not been until recently that these innovative methods have been collectively recognized and achieved an independent status. By eliminating the traditionally employed genetic operators, these probabilistic EAs have been forced to ...
Brian M. Cerny, Chi Zhou, Weimin Xiao, Peter C. Nelson   +3 more
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Gene Expression Programming Ensemble for Classifying Big Datasets

2017
The paper proposes a new GEP-based batch ensemble classifier constructed using the stacked generalization concept. In our approach combination of base classifiers involves evolving the meta-gene using genes induced by GEP from randomly generated combinations of instances with randomly selected subsets of attributes.
Joanna Jȩdrzejowicz, Piotr Jȩdrzejowicz   +1 more
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Temperature prediction by gene expression programming

2023 International Multi-disciplinary Conference in Emerging Research Trends (IMCERT), 2023
Boobphachard Chansawang, Muhammad Waqas, Usa Humphries Wanasing, Phyo Thandar Hlaing, Hnin Aye Lin, Rashid Ali   +5 more
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