首页> 外文会议>2006 BIMW >Correction of Ghost in Reduced ODF with Particle Swarm Optimization Algorithm

【24h】

Correction of Ghost in Reduced ODF with Particle Swarm Optimization Algorithm

机译：粒子群优化算法在ODF精简中的重影校正

获取原文

页面导航

摘要
著录项
相似文献
相关主题

摘要

The particle swarm optimization (PSO) algorithm is introduced into ghost correction, which is also compared with the NMS algorithm. With linear regression correlation factor as evaluation parameter, it is found that both algorithms have the same quality for model ODF, but when it comes to complicated textures, the PSO algorithm shows high ODF fitting quality. It is also demonstrates that the ghost peaks in the reduced ODF can be excluded out in the true ODF from PSO components with both even and odd terms in the series expansion method.

机译：将粒子群优化（PSO）算法引入到幻影校正中，并将其与NMS算法进行比较。以线性回归相关因子作为评估参数，发现两种算法对模型ODF的质量相同，但是对于复杂的纹理，PSO算法显示出较高的ODF拟合质量。还证明了在串联扩展方法中，偶数和奇数项都可以从PSO分量中将还原后的ODF中的重影峰排除在真正的ODF中。

著录项

来源
《2006 BIMW》|2007年|P.10091014|共2页
会议地点
作者
Jian-Guo Tang; Xin-Ming Zhang; Yun-Lai Deng; Zhuo-Ping Zhou;
展开▼
作者单位

展开▼
会议组织
原文格式 PDF
正文语种
中图分类工程材料一般性问题;
关键词
ghost correction; gauss component; texture; particle swarm optimization;

机译：幻影校正高斯分量纹理粒子群优化;

相似文献

外文文献
中文文献
专利

1. Optimization of Laser Ablation Technology for PDPhSM Matrix Nanocomposite Thin Film by Artificial Neural Networks-particle Swarm AlgorithmOptimization of Laser Ablation Technology for PDPhSM Matrix Nanocomposite Thin Film by Artificial Neural Networks-particle Swarm AlgorithmOptimization of Laser Ablation Technology for PDPhSM Matrix Nanocomposite Thin Film by Artificial Neural Networks-particle Swarm Algorithm [J] . TANG Puhong, SONG Renguo, CHAI Guozhong, 武汉理工大学学报：材料科学英文版 . 2010,第002期

机译：人工神经网络优化PDPhSM纳米复合薄膜的激光烧蚀技术-粒子群算法人工神经网络优化PDPhSM纳米复合薄膜的激光烧蚀技术-人工神经网络优化PDPhSM纳米复合薄膜的激光烧蚀技术网络粒子群算法
2. Application of Artificial Neural Network-Particle Swarm Optimization Algorithm for Prediction of Gas Condensate Dew Point Pressure and Comparison With Gaussian Processes Regression-Particle Swarm Optimization Algorithm [J] . Abbas Khaksar Manshad, Habib Rostami, Seyed Moein Hosseini, Journal of Energy Resources Technology . 2016,第3期

机译：人工神经网络-粒子群算法在气体凝结露点压力预测中的应用及与高斯回归的比较-粒子群算法
3. Hybrid: Particle Swarm Optimization-Genetic Algorithm and Particle Swarm Optimization-Shuffled Frog Leaping Algorithm for long-term generator maintenance scheduling [J] . G. Giftson Samuel, C. Christober Asir Rajan International Journal of Electrical Power & Energy Systems . 2015,第feba期

机译：混合：用于长期发电机维护计划的粒子群优化遗传算法和粒子群优化蛙跳算法
4. Correction of Ghost in Reduced ODF with Particle Swarm Optimization Algorithm [C] . Jian-Guo Tang, Xin-Ming Zhang, Yun-Lai Deng, Conference on Beijing International Materials Week . 2007

机译：用粒子群优化算法纠正鬼魂减少的ODF
5. Explorations in swarm algorithms: Hybrid particle swarm optimization and adaptive culture model algorithms. [D] . Noel, Mathew M. 2005

机译：群算法的探索：混合粒子群优化和自适应文化模型算法。
6. A Novel Crow Swarm Optimization Algorithm (CSO) Coupling Particle Swarm Optimization (PSO) and Crow Search Algorithm (CSA) [O] . Ying-Hui Jia, Jun Qiu, Zhuang-Zhuang Ma, 2021

机译：一种新型乌克群优化算法（CSO）耦合粒子群优化（PSO）和乌鸦搜索算法（CSA）
7. Cash balance management: A comparison between genetic algorithms and particle swarm optimization=Gerenciamento do saldo de caixa: uma comparação entre algoritmos genéticos e particle swarm optimization [O] . Marcelo Seido Nagano, Marcelo Botelho da Costa Moraes 2012

机译：现金余额管理：遗传算法与粒子群优化之间的比较= Gerenciamento do saldo de caixa：umacomparaçãoentrealgoritmosgenéticose粒子群算法

Correction of Ghost in Reduced ODF with Particle Swarm Optimization Algorithm

摘要

著录项

相似文献

相关主题

期刊订阅