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; Third International Ying Tan,Yuhui Shi,Zhen Ji Conference proceedings 2012 Springer-Verlag Berlin Heidelbe

[復(fù)制鏈接]
樓主: 嬉戲
51#
發(fā)表于 2025-3-30 10:25:16 | 只看該作者
52#
發(fā)表于 2025-3-30 15:29:06 | 只看該作者
53#
發(fā)表于 2025-3-30 19:23:00 | 只看該作者
54#
發(fā)表于 2025-3-30 23:04:17 | 只看該作者
Swarm Intelligence Supported e-Remanufacturingtion in the behavior of swarms of insects or other animals. After applied in other fields with success, SI started to gather the interest of researchers working in the field of remanufacturing. In this paper we provide a survey of SI methods that have been used in e-remanufacturing.
55#
發(fā)表于 2025-3-31 02:15:13 | 只看該作者
Quantum-Behaved Particle Swarm Optimization Algorithm Based on Border Mutation and Chaos for Vehiclees to enhance the optimization ability of the algorithm, avoid getting into local optimum and premature convergence. To thosecross-border particles,mutation strategy is used to increase the variety of swarm and strengthen the global search capability. This algorithm is applied to vehicle routing problem to achieve good results.
56#
發(fā)表于 2025-3-31 05:57:09 | 只看該作者
Training ANFIS Parameters with a Quantum-behaved Particle Swarm Optimization Algorithm) for training the parameters of an ANFIS. The ANFIS trained by the proposed method is applied to nonlinear system modeling and chaotic prediction. The simulation results show that the ANFIS-QPSO method performs much better than the original ANFIS and the ANFIS-PSO method.
57#
發(fā)表于 2025-3-31 11:14:50 | 只看該作者
58#
發(fā)表于 2025-3-31 13:43:16 | 只看該作者
A SI-Based Algorithm for Structural Damage Detectionl of 3-storey steel frame structure made in laboratory. Some illustrated results show that the proposed method is very suitable for the structural multi-damage identification, which also show that the SI-based algorithm for structural damage detection can provide an effective and robust tool in the SHM field.
59#
發(fā)表于 2025-3-31 17:37:59 | 只看該作者
60#
發(fā)表于 2025-4-1 00:11:41 | 只看該作者
Grey-Based Particle Swarm Optimization Algorithm may differ for different particles. The proposed PSO algorithm is applied to solve the optimization problems of twelve test functions for illustration. Simulation results are compared with the other three variants of PSO to demonstrate the search performance of the proposed algorithm.
 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(diǎn)評(píng) 投稿經(jīng)驗(yàn)總結(jié) SCIENCEGARD IMPACTFACTOR 派博系數(shù) 清華大學(xué) Yale Uni. Stanford Uni.
QQ|Archiver|手機(jī)版|小黑屋| 派博傳思國際 ( 京公網(wǎng)安備110108008328) GMT+8, 2025-10-22 17:30
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
新丰县| 舞阳县| 嘉善县| 苏尼特右旗| 景德镇市| 望谟县| 通河县| 二连浩特市| 宜宾县| 新化县| 丰原市| 化州市| 鹤山市| 云梦县| 建平县| 泰宁县| 永济市| 临沭县| 阿城市| 尼勒克县| 河东区| 灵台县| 桂东县| 灵丘县| 安宁市| 偃师市| 东城区| 丹凤县| 济南市| 金塔县| 敖汉旗| 桓台县| 鹤庆县| 平潭县| 宜宾县| 东乡| 齐河县| 临澧县| 筠连县| 尼木县| 逊克县|