机构

• 长春光学精密机械与物... [2]
• 大连化学物理研究所 [1]

采集方式

• OAI收割 [3]

内容类型

• 会议论文 [2]
• 期刊论文 [1]

发表日期

• 2008 [2]
• 2007 [1]

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 Application of LIBS technology to the rapid measure of heavy metal contamination in soils 期刊论文  OAI收割 progress in chemistry, 2008, 卷号: 20, 期号: 7-8, 页码: 1165-1171 作者:  Wang Jianwei;  Zhang Nazhen;  Hou Keyong;  Li Haiyang 收藏  |  浏览/下载：46/0  |  提交时间：2015/11/12 laser-induced breakdown spectroscopy(LIBS)  heavy metal contamination  soils  rapid measure   Autofocusing technique based on image processing for remote-sensing camera (EI CONFERENCE) 会议论文  OAI收割 International Symposium on Photoelectronic Detection and Imaging 2007 - Image Processing, September 9, 2007 - September 12, 2007, Beijing, China 作者:  Wang X.;  Xu S.-Y.;  Wang X.;  Wang X. 收藏  |  浏览/下载：22/0  |  提交时间：2013/03/25 The key to the auto-focusing technique based on image processing is the selection of focus measure reflecting image definition. Usually the measures derived are on the premise of the images acquired with the same scene. As for the remote-sensing camera working in linear CCD push-broom imaging mode  the premise doesn't exist because the scenes shot are different at any moment  which brings about difficulties to the selection of the focus measure. To evaluate the image definition  the focus measure based on blur estimation for rough adjustment is proposed to estimate the focused position by only two different lens positions  which greatly saves the auto-focusing time. Another evaluation function based on edge sharpness is developed to find best imaging position in the narrow range. Simulations show that the combination of the two measures has the advantages of rapid reaction and high accuracy.   An improved discrete particle swarm optimization algorithm for TSP (EI CONFERENCE) 会议论文  OAI收割 2007 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology - Workshops, WI-IAT Workshops 2007, November 2, 2007 - November 5, 2007, Silicon Valley, CA, United states 作者:  Wang Y.;  Wang Y.;  Wang Y.;  Wang Y.;  Wang Y. 收藏  |  浏览/下载：28/0  |  提交时间：2013/03/25 An Improved discrete particle swarm optimization (DPSO)-based algorithm for the traveling salesman problem (TSP) is proposed. In order to overcome the problem of premature convergence  a novel depressor is proposed and a diversity measure to control the swarm is also introduced which can be used to switch between the attractor and depressor. The proposed algorithm has been applied to a set of benchmark problems and compared with the existing algorithms for solving TSP using swarm intelligence. The results show that it can prevent premature convergence to a high degree  but still keeps a rapid convergence like the basic DPSO. 2007 IEEE.