模糊非基因信息記憶的雙克隆選擇算法

宋丹; 樊曉平; 文中華; 黃大足; 屈喜龍

doi:10.11999/JEIT160359

模糊非基因信息記憶的雙克隆選擇算法

doi: 10.11999/JEIT160359

2.
(湖南工程學(xué)院計(jì)算機(jī)與通信學(xué)院湘潭 411104) ②(中南大學(xué)信息科學(xué)與工程學(xué)院長(zhǎng)沙 410083) ③(湖南財(cái)政經(jīng)濟(jì)學(xué)院信息管理系長(zhǎng)沙 410205)

基金項(xiàng)目:

國(guó)家自然科學(xué)基金(61272295, 61673164, 61402540)，湖南省自然科學(xué)基金(2016JJ6031, 2016JJ2040)，湖南省教育廳科學(xué)研究項(xiàng)目(16A049, 13A010)

計(jì)量
- 文章訪(fǎng)問(wèn)數(shù): 1470
- HTML全文瀏覽量: 126
- PDF下載量: 559
- 被引次數(shù): 0
出版歷程
- 收稿日期: 2016-04-14
- 修回日期: 2016-09-20
- 刊出日期: 2017-02-19

Double Clonal Selection Algorithm Based on Fuzzy Non-genetic Information Memory

2.
(College of Computer and Communication, Hunan Institute of Engineering, Xiangtan 411104, China)

Funds:

The National Natural Science Foundation of China (61272295, 61673164, 61402540), The Natural Science Foundation of Hunan Province (2016JJ6031, 2016JJ2040), The Scientific Research Fund of Hunan Provincial Education Department (16A049, 13A010)

摘要

摘要: 該文針對(duì)傳統(tǒng)智能優(yōu)化算法中虛擬碰撞而導(dǎo)致的全局搜索效率降低的問(wèn)題，提出一種模糊非基因信息記憶的雙克隆選擇算法。該算法設(shè)計(jì)基于模糊非基因信息的搜索機(jī)制與克隆選擇原理相結(jié)合，對(duì)抗體進(jìn)化中的非基因信息進(jìn)行采集、模糊化并保存到記憶庫(kù)，運(yùn)用這些信息引導(dǎo)該抗體后續(xù)的雙克隆搜索過(guò)程，從而減少非優(yōu)區(qū)域的虛擬碰撞，提高全局搜索效率。通過(guò)標(biāo)準(zhǔn)測(cè)試函數(shù)的仿真試驗(yàn)并與其他算法比較，新算法表現(xiàn)出更快的全局收斂速度和更高的全局收斂精度。
- 克隆選擇 /
- 智能記憶 /
- 模糊信息 /
- 數(shù)值優(yōu)化
Abstract: To provide a better solution for search efficiency reduction problem caused by pseudo collision in the traditional intelligent optimization algorithms, this paper proposes a double clonal selection algorithm based on fuzzy non-genetic information memory. By combing with clonal selection theory, the search mechanism based on fuzzy non-genetic information memory is well performed. The non-genetic information in antibody evolution is collected, fuzzified and stored in the memory. Using this information to guide the subsequent double cloning search process, it can reduce the pseudo collision in non-optimal area, thus the global search efficiency is improved greatly. Extensive simulations show that the proposed algorithm has fast global convergence rate and high global convergence accuracy. Comparative results further demonstrate that it performs better than existing algorithms.
- Clonal selection /
- Intelligent memory /
- Fuzzy information /
- Numerical optimization

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參考文獻(xiàn)(26)

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