| Autor: |
Da Qing Liao, Li Fang Kong, Xin Bin Liu |
| Rok vydání: |
2012 |
| Předmět: |
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| Zdroj: |
Applied Mechanics and Materials. :136-140 |
| ISSN: |
1662-7482 |
| Popis: |
An adaptive genetic algorithm was proposed to optimization bound in order to speed up the convergence of Gaussian mean shift. In practical question, as it's difficult to give a critical value definitely. According to the engine nonlinear of the corresponding oil and performance parameters, in gradient genetic algorithm, BP algorithm of local search is introduced. The adaptive value of chromosomes group gets quickly improved with the search in one coding field getting avoided due to the utilization of knowledge of chromosomes in problem-domain. The crossover and mutation operations are added so that chromosomes will not fall into the local minimum point in neighborhood. The experimental results prove that the convergence speed of the proposed method is non-linear and the use of gradient genetic algorithm is a fast algorithm that can support the global optimization of chromosomes in a group of process of iteration. |
| Databáze: |
OpenAIRE |
| Externí odkaz: |
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