| 查看: 391 | 回复: 2 | ||
| 本帖产生 1 个 ，点击这里进行查看 | ||
| 当前只显示满足指定条件的回帖，点击这里查看本话题的所有回帖 | ||
miller5356金虫 (小有名气)
|
[求助]
帮忙查查这篇文献检索情况
|
|
|
题目:Optimal Test Selection of Complex Electronic Systems Based on Improved Discrete Particle Swarm Optimization Algorithm 作者:Ling Ma, Haijun Li, Xiaofeng Lv [ 发自手机版 https://muchong.com/3g ] |
回复此楼» 猜你喜欢
售SCI一区文章，我:8.O.551.O.5.4,科目全,可伽急
已经有5人回复
-
售SCI一区T0P文章，我:8.O.55.1.O.5.4,科目全,可+急
已经有5人回复
-
售SCI一区T0P文章，我:8.O.55.1.O.5.4,科目全,可+急
已经有4人回复
-
售SCI一区T0P文章，我:8O.55.1.O.5.4,科目齐全,可+急
已经有4人回复
-
2026年8月25日国自然放榜前突然收到列入评审专家邮件，有关系吗？
已经有20人回复
-
今天务委会开完了，明天出结果吗
已经有22人回复
-
在坚冰还盖着北海的时候，我看到了怒放的梅花。
已经有9人回复
-
明天应该可查了！？
已经有6人回复
-
有没有大神帮我看看基金代码
已经有10人回复
-
放榜前的不淡定
已经有19人回复
baiyuefei
版主 (文学泰斗)
风雪
- 应助: 4643 (副教授)
- 贵宾: 46.97
- 金币: 659204
- 散金: 11616
- 红花: 995
- 沙发: 81
- 帖子: 69600
- 在线: 13498.6小时
- 虫号: 676696
- 注册: 2008-12-18
- 性别: GG
- 专业: 合成药物化学
- 管辖: 有机交流
3楼2016-03-30 18:24:22
baiyuefei
版主 (文学泰斗)
风雪
- 应助: 4643 (副教授)
- 贵宾: 46.97
- 金币: 659204
- 散金: 11616
- 红花: 995
- 沙发: 81
- 帖子: 69600
- 在线: 13498.6小时
- 虫号: 676696
- 注册: 2008-12-18
- 性别: GG
- 专业: 合成药物化学
- 管辖: 有机交流
【答案】应助回帖
★ ★ ★ ★ ★ ★ ★ ★ ★ ★
感谢参与，应助指数 +1
miller5356: 金币+10, ★★★★★最佳答案 2016-03-30 19:22:49
感谢参与，应助指数 +1
miller5356: 金币+10, ★★★★★最佳答案 2016-03-30 19:22:49
|
EI检索： Accession number: 20153201154068 Title: Optimal test selection of complex electronic systems based on improved discrete particle swarm optimization algorithm Authors: Ma, Ling1 ; Li, Haijun1 ; Lv, Xiaofeng1 Author affiliation: 1Naval Aeronautical and Astronautical University, Yantai, China Corresponding author: Ma, Ling Source title: Lecture Notes in Electrical Engineering Abbreviated source title: Lect. Notes Electr. Eng. Volume: 334 Issue date: 2015 Publication year: 2015 Pages: 549-557 Language: English ISSN: 18761100 E-ISSN: 18761119 Document type: Journal article (JA) Publisher: Springer Verlag Abstract: Optimal test selection is the important content of complex electronic system testability design. This chapter establishes the mathematical model of optimal test selection and then proposes an improved discrete particle swarm optimization algorithm to provide a solution. The algorithm designs a new fitness function according to the characteristics of test selection. In order to avoid the local optimum, an inertia weight adaptive adjustment strategy based on the group’s premature degree is proposed. The simulation results show that the algorithm proposed can achieve a global optimal solution fast and effectively. Optimization results meet all system requirements and can provide an effective guidance for optimal test selection of complex electronic systems. © Springer International Publishing Switzerland 2015. Number of references: 14 Main heading: Algorithms Controlled terms: Electronic guidance systems - Optimization - Particle swarm optimization (PSO) Uncontrolled terms: Algorithm design - Complex electronic systems - Discrete particle swarm optimization algorithm - Fitness functions - Global optimal solutions - System requirements - Test selection - Testability designs Classification code: 715.1 Electronic Equipment, non-communication - 723 Computer Software, Data Handling and Applications - 921 Mathematics - 921.5 Optimization Techniques DOI: 10.1007/978-3-319-13707-0_60 Database: Compendex Compilation and indexing terms, © 2016 Elsevier Inc. |
2楼2016-03-30 18:24:08
28