找回密碼
 To register

QQ登錄

只需一步,快速開始

掃一掃,訪問微社區(qū)

打印 上一主題 下一主題

Titlebook: Evolutionary Algorithms, Swarm Dynamics and Complex Networks; Methodology, Perspec Ivan Zelinka,Guanrong Chen Book 2018 Springer-Verlag Gmb

[復制鏈接]
查看: 53952|回復: 52
樓主
發(fā)表于 2025-3-21 17:10:44 | 只看該作者 |倒序瀏覽 |閱讀模式
書目名稱Evolutionary Algorithms, Swarm Dynamics and Complex Networks
副標題Methodology, Perspec
編輯Ivan Zelinka,Guanrong Chen
視頻videohttp://file.papertrans.cn/318/317818/317818.mp4
概述Includes recent research in Complex Networks and Evolutionary Dynamics.Highlights the mutual relations between the dynamics of evolutionary algorithms, complex networks, and CML (Coupled Map Lattices)
叢書名稱Emergence, Complexity and Computation
圖書封面Titlebook: Evolutionary Algorithms, Swarm Dynamics and Complex Networks; Methodology, Perspec Ivan Zelinka,Guanrong Chen Book 2018 Springer-Verlag Gmb
描述.Evolutionary algorithms constitute a class of well-known algorithms, which are designed based on the Darwinian theory of evolution and Mendelian theory of heritage. They are partly based on random and partly based on deterministic principles. Due to this nature, it is challenging to predict and control its performance in solving complex nonlinear problems. Recently, the study of evolutionary dynamics is focused not only on the traditional investigations but also on the understanding and analyzing new principles, with the intention of controlling and utilizing their properties and performances toward more effective real-world applications. In this book, based on many years of intensive research of the authors, is proposing novel ideas about advancing evolutionary dynamics towards new phenomena including many new topics, even the dynamics of equivalent social networks. In fact, it includes more advanced complex networks and incorporates them with the CMLs (coupled map lattices), whichare usually used for spatiotemporal complex systems simulation and analysis, based on the observation that chaos in CML can be controlled, so does evolution dynamics. All the chapter authors are, to the
出版日期Book 2018
關(guān)鍵詞Complex Networks; Coupled Map Lattices; Evolutionary Algorithms; Evolutionary Dynamics; spatiotemporal D
版次1
doihttps://doi.org/10.1007/978-3-662-55663-4
isbn_softcover978-3-662-57247-4
isbn_ebook978-3-662-55663-4Series ISSN 2194-7287 Series E-ISSN 2194-7295
issn_series 2194-7287
copyrightSpringer-Verlag GmbH Germany 2018
The information of publication is updating

書目名稱Evolutionary Algorithms, Swarm Dynamics and Complex Networks影響因子(影響力)




書目名稱Evolutionary Algorithms, Swarm Dynamics and Complex Networks影響因子(影響力)學科排名




書目名稱Evolutionary Algorithms, Swarm Dynamics and Complex Networks網(wǎng)絡(luò)公開度




書目名稱Evolutionary Algorithms, Swarm Dynamics and Complex Networks網(wǎng)絡(luò)公開度學科排名




書目名稱Evolutionary Algorithms, Swarm Dynamics and Complex Networks被引頻次




書目名稱Evolutionary Algorithms, Swarm Dynamics and Complex Networks被引頻次學科排名




書目名稱Evolutionary Algorithms, Swarm Dynamics and Complex Networks年度引用




書目名稱Evolutionary Algorithms, Swarm Dynamics and Complex Networks年度引用學科排名




書目名稱Evolutionary Algorithms, Swarm Dynamics and Complex Networks讀者反饋




書目名稱Evolutionary Algorithms, Swarm Dynamics and Complex Networks讀者反饋學科排名




單選投票, 共有 0 人參與投票
 

0票 0%

Perfect with Aesthetics

 

0票 0%

Better Implies Difficulty

 

0票 0%

Good and Satisfactory

 

0票 0%

Adverse Performance

 

0票 0%

Disdainful Garbage

您所在的用戶組沒有投票權(quán)限
沙發(fā)
發(fā)表于 2025-3-21 22:02:13 | 只看該作者
板凳
發(fā)表于 2025-3-22 01:37:57 | 只看該作者
地板
發(fā)表于 2025-3-22 05:17:45 | 只看該作者
5#
發(fā)表于 2025-3-22 12:39:03 | 只看該作者
Sandro Longo,Maria Giovanna Tandaent trend of adaptive and learning methods for improving the performance of evolutionary computational techniques. It seems very likely that the complex network and its statistical characteristics can be used within those adaptive approaches. The network analysis also provides usefull insight into t
6#
發(fā)表于 2025-3-22 13:43:01 | 只看該作者
7#
發(fā)表于 2025-3-22 19:42:15 | 只看該作者
Eskalation und Deeskalation von Commitments on the experimental investigations on the time development and influence of different randomization types, different strategies for Differential Evolution (DE) through the analysis of complex network as a record of population dynamics and indices selection. The population is visualized as an evolvi
8#
發(fā)表于 2025-3-22 22:52:23 | 只看該作者
9#
發(fā)表于 2025-3-23 02:21:22 | 只看該作者
10#
發(fā)表于 2025-3-23 08:26:04 | 只看該作者
 關(guān)于派博傳思  派博傳思旗下網(wǎng)站  友情鏈接
派博傳思介紹 公司地理位置 論文服務(wù)流程 影響因子官網(wǎng) 吾愛論文網(wǎng) 大講堂 北京大學 Oxford Uni. Harvard Uni.
發(fā)展歷史沿革 期刊點評 投稿經(jīng)驗總結(jié) SCIENCEGARD IMPACTFACTOR 派博系數(shù) 清華大學 Yale Uni. Stanford Uni.
QQ|Archiver|手機版|小黑屋| 派博傳思國際 ( 京公網(wǎng)安備110108008328) GMT+8, 2025-10-25 12:45
Copyright © 2001-2015 派博傳思   京公網(wǎng)安備110108008328 版權(quán)所有 All rights reserved
快速回復 返回頂部 返回列表
呼伦贝尔市| 邢台市| 安塞县| 遂宁市| 五寨县| 榆林市| 莫力| 渭源县| 惠安县| 长汀县| 民勤县| 玉溪市| 石渠县| 南召县| 萨嘎县| 炎陵县| 平昌县| 平武县| 耿马| 休宁县| 泸州市| 盐边县| 三河市| 惠来县| 叙永县| 达日县| 丹阳市| 南川市| 石景山区| 凤台县| 百色市| 乐至县| 天全县| 海丰县| 武宁县| 商河县| 双江| 巨鹿县| 西藏| 夹江县| 宁乡县|