机构

• 金属研究所 [1]
• 地理科学与资源研究所 [1]
• 长春光学精密机械与物... [1]

采集方式

• OAI收割 [3]

内容类型

• 期刊论文 [2]
• 会议论文 [1]

发表日期

• 2021 [1]
• 2009 [2]

学科主题

筛选

浏览/检索结果: 共3条，第1-3条 帮助 条数/页： 5101520253035404550556065707580859095100 排序方式： 请选择题名升序题名降序提交时间升序提交时间降序作者升序作者降序发表日期升序发表日期降序 A GIS-Based Multi-Criterion Decision-Making Method to Select City Fire Brigade: A Case Study of Wuhan, China 期刊论文  OAI收割 ISPRS INTERNATIONAL JOURNAL OF GEO-INFORMATION, 2021, 卷号: 10, 期号: 11, 页码: 26 作者:  Jiang, Yuncheng;  Lv, Aifeng;  Yan, Zhigang;  Yang, Zhen   |  收藏  |  浏览/下载：18/0  |  提交时间：2022/09/21 spatial optimization  point of interest  potential fire-risk zone  multi-criterion decision-making  traffic situation   Using bidirectional binary particle swarm optimization for feature selection in feature-level fusion recognition system (EI CONFERENCE) 会议论文  OAI收割 2009 4th IEEE Conference on Industrial Electronics and Applications, ICIEA 2009, May 25, 2009 - May 27, 2009, Xi'an, China 作者:  Wang D.;  Wang Y.;  Wang Y.;  Wang Y.;  Wang Y. 收藏  |  浏览/下载：24/0  |  提交时间：2013/03/25 In feature-level fusion recognition system  the other is optimizing system sensor design to get outstanding cost performance. So feature selection become usually necessary to reduce dimensionality of the combination of multi-sensor features and improve system performance in system design. In general  there are two main missions. One is improving the recognition correct rate as soon as possible  the optimization is usually applied to feature selection because of its computational feasibility and validity. For further improving recognition accuracy and reducing selected feature dimensions  this paper presents a more rational and accurate optimization  Bidirectional Binary Particle Swarm Optimization (BBPSO) algorithm for feature selection in feature-level fusion target recognition system. In addition  we introduce a new evaluating function as criterion function in BBPSO feature selection method. At the last  we utilized Leave-One-Out method to validate the proposed method. The experiment results show that the proposed algorithm improves classification accuracy by two percentage points  while the selected feature dimensions are less one dimension than original Particle Swarm Optimization approach with 16 original feature dimensions. 2009 IEEE.   Couplings in Multi-criterion Aerodynamic Optimization Problems Using Adjoint Methods and Game Strategies 期刊论文  OAI收割 CHINESE JOURNAL OF AERONAUTICS, 2009, 卷号: 22, 期号: 1, 页码: 1-8 作者:  Tang Zhili;  Dong Jun   |  收藏  |  浏览/下载：21/0  |  提交时间：2021/02/26 DESIGN  multi-criterion optimization  aerodynamics  adjoint methods  game strategies  Nash game  Stackelberg game  Pareto front