| 5 | 1/1 | 返回列表 |
| 查看: 621 | 回復(fù): 4 | |||
| 本帖產(chǎn)生 1 個(gè) ,點(diǎn)擊這里進(jìn)行查看 | |||
peng_weishi新蟲 (初入文壇)
|
[交流]
查wos
|
||
|
multi-objective particle optimization algorithm based on sharing-learning and dynamic cording distance 發(fā)自小木蟲Android客戶端 |
木蟲 (文學(xué)泰斗)
|
Multi-objective particle optimization algorithm based on sharing-learning and dynamic crowding distance 作者 eng, G (Peng, Guang)[ 1 ] ; Fang, YW (Fang, Yang-Wang)[ 1 ] ; Peng, WS (Peng, Wei-Shi)[ 1 ] ; Chai, D (Chai, Dong)[ 1 ] ; Xu, Y (Xu, Yang)[ 1 ]OPTIK 卷: 127 期: 12 頁: 5013-5020 DOI: 10.1016/j.ijleo.2016.02.045 出版年: 2016 查看期刊信息 摘要 A multi-objective particle swarm optimization algorithm, based on share-learning and dynamic crowding distance (MOPSO-SDCD), is proposed to improve the convergence accuracy and keep the diversity of the Pareto optimal solutions. First, the sharing-learning factor is applied to modify the velocity updating formulas, which improves both the global search ability and local search accuracy of the algorithm. Meanwhile, Gaussian mutation and greedy strategy are adopted to update personal best position and external archive, which make the algorithm approximate the Pareto front quickly and avoid premature convergence. Finally, MOPSO-SDCD maintains the external archive based on dynamic crowding distance sorting strategy, whose purpose is boosting the diversity and distribution of Pareto optimal solutions. The ZDT series test functions are used to test the performance of MOPSO-SDCD and compare with other three typical algorithms. Simulation results verify the superiority and effectiveness of the proposed algorithm. (C) 2016 Elsevier GmbH. All rights reserved. 關(guān)鍵詞 作者關(guān)鍵詞:Multi-objective optimization; Particle swarm optimization; Sharing-learning; Gaussian mutation; Dynamic crowding distance KeyWords Plus:SWARM OPTIMIZER 作者信息 通訊作者地址: Peng, G (通訊作者) Air Force Engn Univ, Aeronaut & Astronaut Engn Coll, Baling Rd 1, Xian, Peoples R China. 地址: [ 1 ] Air Force Engn Univ, Aeronaut & Astronaut Engn Coll, Baling Rd 1, Xian, Peoples R China 電子郵件地址:pg1445334307@163.com 出版商 ELSEVIER GMBH, URBAN & FISCHER VERLAG, OFFICE JENA, P O BOX 100537, 07705 JENA, GERMANY 類別 / 分類 研究方向:Optics Web of Science 類別:Optics 文獻(xiàn)信息 文獻(xiàn)類型:Article 語種:English 入藏號(hào): WOS:000374618900015 ISSN: 0030-4026 期刊信息 目錄: Current Contents Connect® Impact Factor (影響因子): Journal Citation Reports® 其他信息 IDS 號(hào): DK0RC Web of Science 核心合集中的 "引用的參考文獻(xiàn)": 18 Web of Science 核心合集中的 "被引頻次": 0 |

新蟲 (初入文壇)
版主 (知名作家)
命中※注定

新蟲 (初入文壇)
| 5 | 1/1 | 返回列表 |
| 最具人氣熱帖推薦 [查看全部] | 作者 | 回/看 | 最后發(fā)表 | |
|---|---|---|---|---|
|
[考研] 一志愿華東理工大學(xué),080500學(xué)碩,317分,求調(diào)劑 +7 | s1145 2026-03-31 | 7/350 |
|
|---|---|---|---|---|
|
[考研] 一志愿中國科學(xué)院大學(xué)265求調(diào)劑 +6 | 恬淡ye 2026-03-31 | 7/350 |
|
|
[考研] 調(diào)劑求院校招收 +7 | 鶴鯨鴿 2026-03-28 | 7/350 |
|
|
[考研] 293分求調(diào)劑,外語為俄語 +5 | 加一一九 2026-03-31 | 5/250 |
|
|
[考研] 材料求調(diào)劑 一志愿哈工大總分298分,前三科223分 +10 | dongfang59 2026-03-27 | 10/500 |
|
|
[考研] 合肥區(qū)域性重點(diǎn)一本招收調(diào)劑 +4 | 6266jl 2026-03-30 | 4/200 |
|
|
[考研] 303求調(diào)劑 +7 | DLkz1314. 2026-03-30 | 7/350 |
|
|
[考研] 085601材料工程找調(diào)劑 +17 | oatmealR 2026-03-29 | 18/900 |
|
|
[考研] 085600 材料與化工 329分求調(diào)劑 +18 | Mr. Z 2026-03-25 | 19/950 |
|
|
[考研] 322求調(diào)劑 +10 | 宋明欣 2026-03-27 | 10/500 |
|
|
[考研] 一志愿廈門大學(xué)材料工程專碩354找調(diào)劑!! +5 | 貝唄鋇鋇 2026-03-30 | 5/250 |
|
|
[考研] 071010 323 分求調(diào)劑 +3 | Baekzhy 2026-03-27 | 3/150 |
|
|
[碩博家園] 求調(diào)劑 有機(jī)化學(xué)考研356分 +10 | Nadiums 2026-03-25 | 11/550 |
|
|
[考研] 調(diào)劑考研 +3 | 王杰一 2026-03-29 | 3/150 |
|
|
[考研] 312,生物學(xué)求調(diào)劑 +3 | 小譯同學(xué)abc 2026-03-28 | 3/150 |
|
|
[考研] 復(fù)試調(diào)劑 +3 | raojunqi0129 2026-03-28 | 3/150 |
|
|
[考研] 315分求調(diào)劑 +7 | 26考研上岸版26 2026-03-26 | 7/350 |
|
|
[考研] 265求調(diào)劑11408 +3 | 劉小鹿lu 2026-03-27 | 3/150 |
|
|
[考研] 考研一志愿蘇州大學(xué)初始315(英一)求調(diào)劑 +3 | sbdksD 2026-03-24 | 4/200 |
|
|
[考研] 347求調(diào)劑 +4 | L when 2026-03-25 | 4/200 |
|