用户名  找回密码
 To register

QQ登录

只需一步,快速开始

扫一扫,访问微社区

Titlebook: Applications of Evolutionary Computation; 18th European Confer Antonio M. Mora,Giovanni Squillero Conference proceedings 2015 Springer Inte

[复制链接]
楼主: 摇尾乞怜
发表于 2025-3-25 05:26:38 | 显示全部楼层
发表于 2025-3-25 08:27:20 | 显示全部楼层
发表于 2025-3-25 11:51:46 | 显示全部楼层
https://doi.org/10.1007/978-981-287-104-6ovements based on EO aim at better convergence of the algorithm and better quality of program execution in terms of the execution time. The proposed load balancing algorithm is evaluated by experiments with simulated parallelized load balancing of distributed program graphs.
发表于 2025-3-25 18:36:48 | 显示全部楼层
https://doi.org/10.1007/978-981-287-104-6olve the problem using a freely available data set. The results obtained are analysed considering two MO quality metrics: hypervolume and set coverage. After applying a statistical methodology widely accepted, we conclude that SPEA2 provides the best performance on average considering such data set.
发表于 2025-3-25 23:15:34 | 显示全部楼层
James R. Barth,Cindy Lee,Triphon Phumiwasanaures. A broad experimental evaluation on different problems and computational scenarios featuring diverse volatility conditions shows that the combination of these two strategies leads to more robust performances, in particular in situations in which churn rates are large.
发表于 2025-3-26 02:25:13 | 显示全部楼层
Heat Map Based Feature Selection: A Case Study for Ovarian Cancerta without the need of pre-processing, thanks to a built-in compression mechanism based on color quantization. Results shows that our proposal is very competitive against some of the most popular algorithms and succeeds where other methodologies may fail due to the high dimensionality of the data.
发表于 2025-3-26 05:20:59 | 显示全部楼层
A Novel Grouping Genetic Algorithm for Assigning Resources to Users in WCDMA Networks work points out that our GGA approach exhibits a superior performance than that of the conventional method (which minimizes only the load factors), since all users receive the demanded service along with a minimum use of the assigned resources (aggregate capacity, power, and codes).
发表于 2025-3-26 09:42:09 | 显示全部楼层
发表于 2025-3-26 13:37:44 | 显示全部楼层
Planning the Deployment of Indoor Wireless Sensor Networks Through Multiobjective Evolutionary Technolve the problem using a freely available data set. The results obtained are analysed considering two MO quality metrics: hypervolume and set coverage. After applying a statistical methodology widely accepted, we conclude that SPEA2 provides the best performance on average considering such data set.
发表于 2025-3-26 20:51:47 | 显示全部楼层
 关于派博传思  派博传思旗下网站  友情链接
派博传思介绍 公司地理位置 论文服务流程 影响因子官网 SITEMAP 大讲堂 北京大学 Oxford Uni. Harvard Uni.
发展历史沿革 期刊点评 投稿经验总结 SCIENCEGARD IMPACTFACTOR 派博系数 清华大学 Yale Uni. Stanford Uni.
|Archiver|手机版|小黑屋| 派博传思国际 ( 京公网安备110108008328) GMT+8, 2025-6-18 16:17
Copyright © 2001-2015 派博传思   京公网安备110108008328 版权所有 All rights reserved
快速回复 返回顶部 返回列表