| 基于人工鱼群算法和Pearson相关系数的裂缝属性识别 |
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| 引用本文： | 刘廷,田有,朱洪翔,周超,乔汉青.基于人工鱼群算法和Pearson相关系数的裂缝属性识别[J].世界地质,2017,36(1):293-298. |
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| 作者姓名： | 刘廷 田有 朱洪翔 周超 乔汉青 |
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| 作者单位： | 1. 吉林大学 地球探测科学与技术学院, 长春 130026;
2. 中铁二院地勘岩土工程设计研究所, 成都 610031 |
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| 摘 要： | 将人工鱼群算法和Pearson相关系数结合,引入到进行裂缝属性识别的横波分裂方法中。结果表明,本文使用的方法能快速准确地识别裂缝属性,相比于模型空间扫描、粒子群算法及遗传算法等识别方法,收敛速度增快了约3倍,稳定性上也有所提高。
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| 关 键 词： | 横波分裂 人工鱼群算法 裂缝识别 Pearson相关系数 |
| 收稿时间： | 2016-07-08 |
| 修稿时间： | 2016-09-03 |
Fracture property identification based on Artificial Fish-Swarm Algorithm and Pearson correlation coefficients |
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| LIU Ting,TIAN You,ZHU Hong-xiang,ZHOU Chao,QIAO Han-qing.Fracture property identification based on Artificial Fish-Swarm Algorithm and Pearson correlation coefficients[J].World Geology,2017,36(1):293-298. |
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| Authors: | LIU Ting TIAN You ZHU Hong-xiang ZHOU Chao QIAO Han-qing |
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| Institution: | 1. College of Geo-exploration Science and Technology, Jilin University, Changchun 130026, China;
2. China Railway Eryuan Engineering Group CO. LTD, Chengdu 610031, China |
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| Abstract: | In this study, the Artificial Fish-School Algorithm and Pearson correlation coefficient are combined, and introduced into the identification of fracture properties with shear wave splitting method. The results show that the method can effectively and accurately identify the fracture properties. Compared with model space scanning, particle swarm optimization and genetic algorithm, this method has an improved stability and an increased convergence rate which is three times faster. |
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| Keywords: | shear-wave splitting Artificial Fish-School Algorithm fracture identification Pearson correlation coefficients |
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