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lui0822_2009新蟲 (初入文壇)
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[求助]
能否幫我給我論文摘要潤色！謝謝
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We proposed a complex network community discovery method based on parallel immune genetic algorithm for the problem of low efficiency, slow convergence rate and population degradation in community mining method based on genetic algorithm. The algorithm is making use of the principle of parallel immune system to ensure the diversity of population, and enhancing the searching ability by using a single path crossover operator in the initial population and crossover operation, in the initial population and crossover operation to enhance the ability to find the best use of the single path crossover operator, while using the improved character encoding and adaptive mutation operator to further reduce the search space, improve the population degradation phenomenon.Experiments show that the improved parallel immune genetic algorithm is used to find the problem of complex network community with high accuracy, and the effectiveness and efficiency. 發(fā)自小木蟲IOS客戶端 |
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gerryangel
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2樓2016-04-13 19:31:47
lui0822_2009
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針對(duì)基于遺傳算法的社區(qū)挖掘方法中存在運(yùn)行效率低、收斂速度慢、種群退化等問題，提出了一種基于并行免疫遺傳算法的復(fù)雜網(wǎng)絡(luò)社區(qū)發(fā)現(xiàn)方法。利用并行免疫原理引入到選擇操作中保證種群多樣性；在初始化種群和交叉操作中利用單路交叉算子加強(qiáng)尋優(yōu)能力，同時(shí)，采用改進(jìn)的字符編碼和自適應(yīng)變異算子進(jìn)一步有效縮小了搜索空間，改善種群退化現(xiàn)象。實(shí)驗(yàn)表明，使用該改進(jìn)并行免疫遺傳算法用來復(fù)雜網(wǎng)絡(luò)社區(qū)發(fā)現(xiàn)問題具備較高的精度，以及算法的有效性與高效性。 發(fā)自小木蟲IOS客戶端 |
3樓2016-04-15 13:26:43
lui0822_2009
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4樓2016-04-15 13:27:02
【答案】應(yīng)助回帖
★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★
lui0822_2009(fjtony163代發(fā)): 金幣+20, 代發(fā) 2016-05-15 09:45:33
fjtony163: 翻譯EPI+1, 代發(fā) 2016-05-15 09:45:39
lui0822_2009(fjtony163代發(fā)): 金幣+20, 代發(fā) 2016-05-15 09:45:33
fjtony163: 翻譯EPI+1, 代發(fā) 2016-05-15 09:45:39
| To solve the problems of low efficiency, slow convergence rate and population degradation in genetic algorithm-based community mining method, a complex network community discovery method based on parallel immune genetic algorithm was proposed. The algorithm ensures the diversity of population using the principle of parallel immune system, thus enhancing the ability to find the best use of the single path crossover operator in the initial population and crossover operation; furthermore, it reduces the search space using the improved character encoding and adaptive mutation operator, improving the population degradation phenomenon. Experiments show that the improved parallel immune genetic algorithm can be used to find the problems of complex network community with high accuracy, effectiveness and efficiency. |
5樓2016-04-15 14:21:33
lui0822_2009
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6樓2016-04-16 14:03:13
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