维普期刊资源整合服务平台（V6.5）

维普中文期刊产品整合服务

7篇 您的检索式：作者名="Nezafat"

选中清除导出查看参考文献查看引证文献引用追踪共1页首页上一页第1页下一页末页 /1 跳转

		题名	作者	年代	出处	被引量
	1	Bl-insensitive T2 preparation for improved coronary magnetic resonance angiogra- phyat 3 T显示文摘	Nezafat R Stuber M Ouwerkerk R	2006	Magn Reson Med2006，55，4：	1
	2	Delayed-Enhancement Cardiovascular Magnetic Resonance Coronary Artery Wall Imaging显示文摘	Susan B. Yeon Adeel Sabir Melvin Clouse Pedro O. Martinezclark Dana C. Peters Thomas H. Hauser C. Michael Gibson Reza Nezafat David Maintz Warren J. Manning René M. Botnar	2007	Journal of the American College of Cardiology2007，，5：	1
	3	Indoor localization usinga spatial channel signature database 显示文摘	NEZAFAT M KAVEH M TSUJI H	2006	IEEE Antennas andWireless Propagation Letters2006，5，1：	1
	4	Real-time blood flow imaging using autocalibrated spiral sensitivity encoding显示文摘	Kellman P Derbyshire JA	2005	Magn Reson Med2005，54，6：	1
	5	Wavelet-domain medi- cal image denoising using bivariate Laplacian mixture mode显示文摘	Rabbani H Nezafat R Gazor S	2009	IEEE Transactions on Biomedical Enginee- ring2009，56，12：	1
	6	B1-insensitive T2 preparation for improved coronary magnetic resonance angiography at 3 T显示文摘	Nezafat R Stuber M Ouwerkerk R	2006	Magn Reson Med2006，55，4：	1
	7	A comparative study on using meta-heuristic algorithms for road maintenance planning:Insights from field study in a developing country显示文摘Optimized road maintenance planning seeks for solutions that can minimize the life-cycle cost of a road network and concurrently maximize pavement condition. Aiming at proposing an optimal set of road maintenance solutions, robust meta-heuristic algorithms are used in research. Two main optimization techniques are applied including single-objective and multi-objective optimization. Genetic algorithms(GA), particle swarm optimization(PSO), and combination of genetic algorithm and particle swarm optimization(GAPSO) as single-objective techniques are used, while the non-domination sorting genetic algorithm II(NSGAII) and multi-objective particle swarm optimization(MOPSO) which are sufficient for solving computationally complex large-size optimization problems as multi-objective techniques are applied and compared. A real case study from the rural transportation network of Iran is employed to illustrate the sufficiency of the optimum algorithm. The formulation of the optimization model is carried out in such a way that a cost-effective maintenance strategy is reached by preserving the performance level of the road network at a desirable level. So, the objective functions are pavement performance maximization and maintenance cost minimization. It is concluded that multi-objective algorithms including non-domination sorting genetic algorithm II(NSGAII) and multi-objective particle swarm optimization performed better than the single objective algorithms due to the capability to balance between both objectives. And between multi-objective algorithms the NSGAII provides the optimum solution for the road maintenance planning.	Ali Gerami Matin Reza Vatani Nezafat Amir Golroo	2017	Journal of Traffic and Transportation Engineering(English Edition)2017，4，5：	0

返回顶部每页显示：

共1页首页上一页第1页下一页末页 /1 跳转

goolge学术搜索-维普

网站首页 | 关于我们 | 联系我们 | 产品服务 | 客服中心 | 广告服务 | 版权声明 | 网站联盟 | 友情链接 | 售卡网点

版权所有© 渝B2-20050021-1　渝公网安备 50019002500403号　违法和不良信息举报中心

互联网出版许可证新出网证(渝)字10号全国400电话 - 免长途话费