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: Advances in Swarm Intelligence; 10th International C Ying Tan,Yuhui Shi,Ben Niu Conference proceedings 2019 Springer Nature Switzerland AG

[復(fù)制鏈接]
樓主: 萌芽的心
41#
發(fā)表于 2025-3-28 17:39:29 | 只看該作者
42#
發(fā)表于 2025-3-28 19:18:02 | 只看該作者
K. S. Jithin Mohan,S. Paul Sathiyanmportant part of wireless communication systems. An Antenna is a device for transmitting or receiving signals. Antennas can be broadly divided into two types, antenna elements and antenna arrays. Antenna elements function in transmitting or receiving signals. Antenna arrays are actually an array of
43#
發(fā)表于 2025-3-28 23:47:57 | 只看該作者
Concanavalin A: An Introduction,blem. The purpose of this paper is to propose a powerful and easy-to-use multi-objective optimization approach for building energy performance. In this work, an improved multi-objective particle swarm optimization algorithm with less control parameters is proposed and coupled with EnergyPlus buildin
44#
發(fā)表于 2025-3-29 05:48:34 | 只看該作者
https://doi.org/10.1007/978-1-4684-0949-9sengers’ minimum waiting time. This paper proposes an ensemble differential algorithm based on particle swarm optimization (abbreviated as PSOEDE) to solve the VSP. In PSOEDE algorithm, the mutation process is designed by dividing the original process into two parts: the first part combines the PSO
45#
發(fā)表于 2025-3-29 11:00:25 | 只看該作者
46#
發(fā)表于 2025-3-29 13:50:14 | 只看該作者
https://doi.org/10.1057/9781403973474, which was cutting trajectory planning method of roadheader. It could reduce the cost of tunneling, improve the cutting efficiency of coal and rock, and reduced casualties. The improved particle swarm optimization (PSO) is adopt to plan the cutting trajectory and the features of the improvements ar
47#
發(fā)表于 2025-3-29 17:09:20 | 只看該作者
48#
發(fā)表于 2025-3-29 23:06:53 | 只看該作者
Generative Adversarial Optimization is proposed in this paper. This GAO framework sets up generative models to generate candidate solutions via an adversarial process, in which two models are trained alternatively and simultaneously, i.e., a generative model for generating candidate solutions and a discriminative model for estimating
49#
發(fā)表于 2025-3-30 03:48:03 | 只看該作者
Digital Model of Swarm Unit System with Interruptionsion on suddenly appearing dangerous external affects, etc., is considered. It is shown that for the proper planning of computation process in systems with interruption it is necessary to have a model, which permits to predict system state at any time. Approach to simulation, based on the representat
50#
發(fā)表于 2025-3-30 05:32:35 | 只看該作者
Algorithm Integration Behavior for Discovering Group Membership Rules of the assumptions when working with these algorithms is that the complexity of the membership domain of the cases they use does not affect the quality of the obtained results. So, it is important to analyze the behavior of the information exploitation process through the discovery of group members
 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(xué) 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(xué) 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, 2025-10-31 21:51
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(fù) 返回頂部 返回列表
楚雄市| 柘城县| 富民县| 扎鲁特旗| 正安县| 永济市| 东城区| 方城县| 自贡市| 桂林市| 汉川市| 蒙山县| 洪湖市| 玉溪市| 武义县| 龙门县| 如皋市| 鹤庆县| 西峡县| 平谷区| 芦山县| 宁德市| 察隅县| 利辛县| 黔南| 桂林市| 花莲市| 黔江区| 手机| 富裕县| 罗江县| 万源市| 繁峙县| 孟津县| 五华县| 安阳县| 双鸭山市| 江川县| 微博| 平安县| 扎囊县|