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: Engineering Applications of Modern Metaheuristics; Taymaz Akan,Ahmed M. Anter,Diego Oliva Book 2023 The Editor(s) (if applicable) and The

[復制鏈接]
查看: 42017|回復: 50
樓主
發(fā)表于 2025-3-21 16:06:46 | 只看該作者 |倒序瀏覽 |閱讀模式
書目名稱Engineering Applications of Modern Metaheuristics
編輯Taymaz Akan,Ahmed M. Anter,Diego Oliva
視頻videohttp://file.papertrans.cn/311/310703/310703.mp4
概述Provides the reader with the most representative optimization tools used for scientific and engineering problems.Explains the algorithms used, the selected problem, and the implementation.Provides pra
叢書名稱Studies in Computational Intelligence
圖書封面Titlebook: Engineering Applications of Modern Metaheuristics; Taymaz Akan,Ahmed M. Anter,Diego Oliva Book 2023 The Editor(s) (if applicable) and The
描述.This book is a collection of various methodologies that make it possible for metaheuristics and hyper-heuristics to solve problems that occur in the real world. This book contains chapters that make use of metaheuristics techniques. The application fields range from image processing to transmission power control, and case studies and literature reviews are included to assist the reader. Furthermore, some chapters present cutting-edge methods for load frequency control and IoT implementations. In this sense, the book offers both theoretical and practical contents in the form of metaheuristic algorithms. The researchers used several stochastic optimization methods in this book, including evolutionary algorithms and Swarm-based algorithms. The chapters were written from a scientific standpoint. As a result, the book is primarily aimed at undergraduate and postgraduate students of Science, Engineering, and Computational Mathematics, but it can also be used in courses on Artificial Intelligence, among other things. Similarly, the material may be beneficial to research in evolutionary computation and artificial intelligence communities..
出版日期Book 2023
關鍵詞Computational Intelligence; Metaheuristics; Optimization Algorithms; Swarm intelligence; Evolutionary al
版次1
doihttps://doi.org/10.1007/978-3-031-16832-1
isbn_softcover978-3-031-16834-5
isbn_ebook978-3-031-16832-1Series ISSN 1860-949X Series E-ISSN 1860-9503
issn_series 1860-949X
copyrightThe Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl
The information of publication is updating

書目名稱Engineering Applications of Modern Metaheuristics影響因子(影響力)




書目名稱Engineering Applications of Modern Metaheuristics影響因子(影響力)學科排名




書目名稱Engineering Applications of Modern Metaheuristics網(wǎng)絡公開度




書目名稱Engineering Applications of Modern Metaheuristics網(wǎng)絡公開度學科排名




書目名稱Engineering Applications of Modern Metaheuristics被引頻次




書目名稱Engineering Applications of Modern Metaheuristics被引頻次學科排名




書目名稱Engineering Applications of Modern Metaheuristics年度引用




書目名稱Engineering Applications of Modern Metaheuristics年度引用學科排名




書目名稱Engineering Applications of Modern Metaheuristics讀者反饋




書目名稱Engineering Applications of Modern Metaheuristics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限
沙發(fā)
發(fā)表于 2025-3-21 23:42:56 | 只看該作者
Metaheuristic Algorithms in IoT: Optimized Edge Node Localization,proposed hybrid metaheuristic algorithm tries to find the near-optimal solution with high efficiency by using the advantage of both algorithms. At the same time, the shortcomings of each will be eliminated. The proposed algorithm is used to solve the edge computing node localization problem, which i
板凳
發(fā)表于 2025-3-22 01:33:45 | 只看該作者
地板
發(fā)表于 2025-3-22 06:58:18 | 只看該作者
Minimum Transmission Power Control for the Internet of Things with Swarm Intelligence Algorithms,oaches are required for more efficient Internet of Things (IoT) usage. Wireless sensor networks (WSNs) contain energy-limited devices and calculating the minimum transmission power control (TPC) is a tackling process. Swarm intelligence is a subsection of AI and in the last four decades, many swarm
5#
發(fā)表于 2025-3-22 12:43:54 | 只看該作者
6#
發(fā)表于 2025-3-22 14:47:21 | 只看該作者
A Meta-Heuristic Algorithm Based on the Happiness Model,imization algorithm called the happiness optimizer (HPO) algorithm. An HPO algorithm is designed based on personal behavior and demonstrated in 30 and 100 dimensions on benchmark functions. The model includes four questions: “what do you want?”, “what do you have?”, “what do others have?”, and “what
7#
發(fā)表于 2025-3-22 17:07:41 | 只看該作者
8#
發(fā)表于 2025-3-22 23:33:47 | 只看該作者
9#
發(fā)表于 2025-3-23 02:21:55 | 只看該作者
Fitting Curves of Ruminal Degradation Using a Metaheuristic Approach,is inevitable to pay attention to all the needs and nutrient degradability and degradation fraction. This study aimed to investigate the use of particle swarm optimization (PSO) to describe the disappearance curves of . cuts. This paper uses the first-order kinetic model to describe the disappearanc
10#
發(fā)表于 2025-3-23 05:58:57 | 只看該作者
Optimizing a Real Case Assembly Line Balancing Problem Using Various Techniques,re assigned to workstations aiming to minimize the required number of workstations, subject to considering a given production rate and satisfying the precedence relationships between tasks. Besides, line efficiency and smoothness index are considered as the second and the third objectives to select
 關于派博傳思  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 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, 2025-10-23 21:01
Copyright © 2001-2015 派博傳思   京公網(wǎng)安備110108008328 版權所有 All rights reserved
快速回復 返回頂部 返回列表
奎屯市| 濉溪县| 宝应县| 济阳县| 金秀| 蓝田县| 密山市| 驻马店市| 嘉兴市| 黔西县| 华阴市| 秀山| 连州市| 辉县市| 红桥区| 阳泉市| 荣成市| 荃湾区| 江陵县| 遵义县| 辉南县| 松滋市| 永宁县| 济宁市| 建始县| 绿春县| 宁海县| 闻喜县| 顺义区| 惠来县| 老河口市| 长岭县| 铜川市| 灌南县| 淮滨县| 嘉鱼县| 淮南市| 九寨沟县| 阳泉市| 渭源县| 江川县|