Results of Genetic Evolutionary Algorithms (GEA)
Top PDF Results of Genetic Evolutionary Algorithms (GEA):
Genetic Algorithms and Programming-An Evolutionary Methodology
... the genetic programming paradigm is an important characteristic of the genetic ...The results of this genetic programming methodology process are inherently ...
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1 Evolutionary Computation: from Genetic Algorithms to Genetic Programming
... any evolutionary computation technique, the generation of first population of individuals is important for successful imple- mentation of ...of genetic programming are that no analytical knowledge is needed ...
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Evolutionary Algorithms using Evolutionary Algorithms
... Intelligence, Evolutionary Algorithm, Genetic ...of Evolutionary Algorithm is Search ...of evolutionary algorithms for faster and better evaluation of ...previous results. It ...
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A comparison of genetic algorithms and evolutionary programming in conceptual software design
... 10 evolutionary searches have been conducted, the population being initialized at random prior to each evolutionary ...the evolutionary search, “convergence” occurred if one or more individuals of ...
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Theory grounded design of genetic programming and parallel evolutionary algorithms
... of Genetic Programming, we have stated that there are two leading ...proper Genetic Programming evolving functions ...quantitative results on the ...of evolutionary algorithms, can ...
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Affine image registration using genetic algorithms and evolutionary strategies
... of evolutionary algorithms to align two or more 2-D images by means of image ...well-known evolutionary algorithms (EAs), the genetic algorithm (GA) as well as the evolutionary ...
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Standard Steady State Genetic Algorithms Can Hillclimb Faster than Mutation-only Evolutionary Algorithms
... the results show that the greedy selection/greedy crossover GA is slightly faster than the greedy parent selection GA and that greedy parent selection is slightly faster than standard ...
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Robust evolutionary algorithms
... The final test problem was DTrap. SCX’s improvement over traditional crossovers was the least significant on this problem, and required a different configuration to achieve statistically significantly better ...
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Design and application of gene-pool optimal mixing evolutionary algorithms for genetic programming
... The last step of our pipeline repairs possible anatomical inconsistencies present in the assembled phantoms. We automatically compute possible overlaps between the trans- planted OARs (liver and spleen), and between the ...
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Optimization of Feedback Controller in Restructured Power System Using Evolutionary Genetic Algorithms
... problem Evolutionary Genetic algorithms were proposed to optimize the feedback gains of the controller, having access to few of the AGC ...The results obtained by the proposed method are found ...
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On the Robustness of Evolutionary Algorithms to Noise: Refined Results and an Example Where Noise Helps
... valleyž structures, which is an important characteristic of many hard problems from combinatorial optimisation [23, 30]. Prügel-Bennett deined such a class of problems known as Hur- dle problems [24] as an example ...
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Evolutionary Algorithms in Astronautic Applications
... ordinary evolutionary algorithms is to improve their convergence via combination with ...genetic algorithms. With that method the lack of solution precision of genetic algorithms ...
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Applied Evolutionary Algorithms in Java
... 5.10 Evolutionary Methods 82 ...5.13.3 Results 94 ...in Evolutionary Computing 101 6.1 Developments in Evolutionary Algorithms 101 ...Parallel Genetic Programming with Mobile ...
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Evolutionary Algorithms for Definition Extraction
... of genetic programming to learn the typical linguistic forms of definitions and a genetic algorithm to learn the relative im- portance of these ...forms. Results are very posi- tive, showing the ...
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Evolutionary algorithms for timetable problems
... on evolutionary algorithms, which turn out to be useful as a general-purpose optimization tool, due to their high flexibility accompanied by conceptual ...the results of their application to the ...
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Comparison of multi-modal optimization algorithms based on evolutionary algorithms
... standard genetic algorithm and multiple optimal solutions can be ...space. Algorithms are com- pared on hump problems having as many as 25 variables and 50 ...simulation results, conclusions about ...
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Evolutionary Algorithms for
... All algorithms evolved reasonably distributed fronts, although there was a difference in the distance to the Pareto-optimal ...Pareto-based algorithms have advantages here, but only NSGA and SPEA evolved a ...
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Genetic Algorithms Genetic Algorithms
... (Recombination) (Recombination) Crossover Crossover -- Many genetic Many genetic algorithms use strings of binary symbols for algorithms use strings of binary symbols for chromosom[r] ...
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Evolutionary Algorithms in modefrontier
... developed algorithms are robust and efficient • But… • … the design otimisation process, whatever is the algorithm, is not a push-button-get-result process but is a knowledge acquisition, knowledge exploitation, ...
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Evolutionary Algorithms in Astrodynamics
... UAM, Poznan, Poland Abstract This paper presents the method of solving the equations of motions by evolutionary algorithms. Starting from random trajectory, the solution is obtained by accepting the ...
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