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: Genetic Programming Theory and Practice VIII; Rick Riolo,Trent McConaghy,Ekaterina Vladislavleva Book 2011 Springer Science+Business Media

[复制链接]
查看: 34323|回复: 55
发表于 2025-3-21 19:32:32 | 显示全部楼层 |阅读模式
书目名称Genetic Programming Theory and Practice VIII
编辑Rick Riolo,Trent McConaghy,Ekaterina Vladislavleva
视频video
概述Presents large-scale, real-world applications of GP.Addresses a variety of problem domains that respond to GP solutions.Written by leading researchers and practitioners in the field.Includes supplemen
丛书名称Genetic and Evolutionary Computation
图书封面Titlebook: Genetic Programming Theory and Practice VIII;  Rick Riolo,Trent McConaghy,Ekaterina Vladislavleva Book 2011 Springer Science+Business Media
描述.The contributions in this volume are written by the foremost international researchers and practitioners in the GP arena. They examine the similarities and differences between theoretical and empirical results on real-world problems. The text explores the synergy between theory and practice, producing a comprehensive view of the state of the art in GP application..Topics include: FINCH: A System for Evolving Java, Practical Autoconstructive Evolution, The Rubik Cube and GP Temporal Sequence Learning, Ensemble classifiers: AdaBoost and Orthogonal Evolution of Teams, Self-modifying Cartesian GP, Abstract Expression Grammar Symbolic Regression, Age-Fitness Pareto Optimization, Scalable Symbolic Regression by Continuous Evolution, Symbolic Density Models, GP Transforms in Linear Regression Situations, Protein Interactions in a Computational Evolution System, Composition of Music and Financial Strategies via GP, and Evolutionary Art Using Summed Multi-Objective Ranks..Readers will discover large-scale, real-world applications of GP to a variety of problem domains via in-depth presentations of the latest and most significant results in GP ..
出版日期Book 2011
关键词Genetic Programming; Genetic Programming Applications; Genetic Programming Theory; Symbolic regression;
版次1
doihttps://doi.org/10.1007/978-1-4419-7747-2
isbn_softcover978-1-4614-2719-3
isbn_ebook978-1-4419-7747-2Series ISSN 1932-0167 Series E-ISSN 1932-0175
issn_series 1932-0167
copyrightSpringer Science+Business Media, LLC 2011
The information of publication is updating

书目名称Genetic Programming Theory and Practice VIII影响因子(影响力)




书目名称Genetic Programming Theory and Practice VIII影响因子(影响力)学科排名




书目名称Genetic Programming Theory and Practice VIII网络公开度




书目名称Genetic Programming Theory and Practice VIII网络公开度学科排名




书目名称Genetic Programming Theory and Practice VIII被引频次




书目名称Genetic Programming Theory and Practice VIII被引频次学科排名




书目名称Genetic Programming Theory and Practice VIII年度引用




书目名称Genetic Programming Theory and Practice VIII年度引用学科排名




书目名称Genetic Programming Theory and Practice VIII读者反馈




书目名称Genetic Programming Theory and Practice VIII读者反馈学科排名




单选投票, 共有 1 人参与投票
 

0票 0.00%

Perfect with Aesthetics

 

0票 0.00%

Better Implies Difficulty

 

1票 100.00%

Good and Satisfactory

 

0票 0.00%

Adverse Performance

 

0票 0.00%

Disdainful Garbage

您所在的用户组没有投票权限
发表于 2025-3-21 23:59:52 | 显示全部楼层
发表于 2025-3-22 03:38:43 | 显示全部楼层
发表于 2025-3-22 04:34:54 | 显示全部楼层
发表于 2025-3-22 10:37:46 | 显示全部楼层
Symbolic Density Models of One-in-a-Billion Statistical Tails via Importance Sampling and Genetic P to analyze the tradeoff between high-sigma yields and circuit performance. The flow is validated on two modern industrial problems: a bitcell circuit on a 45nm TSMC process, and a sense amp circuit on a 28nm TSMC process.
发表于 2025-3-22 13:07:48 | 显示全部楼层
发表于 2025-3-22 18:18:28 | 显示全部楼层
发表于 2025-3-22 21:59:00 | 显示全部楼层
Das Aufbereiten von Textausgabenety of different problems, and see that SMCGP is able to solve tasks that require scalability and plasticity. We demonstrate how SMCGP is able to produce results that would be impossible for conventional, static Genetic Programming techniques.
发表于 2025-3-23 01:50:09 | 显示全部楼层
Finch: A System for Evolving Java (Bytecode),eral. This is in contrast to existing work that uses restricted subsets of the Java bytecode instruction set as a representation language for individuals in genetic programming. The ability to evolve Java programs will hopefully lead to a valuable new tool in the software engineer’s toolkit.
发表于 2025-3-23 06:10:52 | 显示全部楼层
A Survey of Self Modifying Cartesian Genetic Programming,ety of different problems, and see that SMCGP is able to solve tasks that require scalability and plasticity. We demonstrate how SMCGP is able to produce results that would be impossible for conventional, static Genetic Programming techniques.
 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, 2025-5-22 12:41
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