中国科学院机构知识库网格系统: 检索

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	Graph matching based on fast normalized cut and multiplicative update mapping 期刊论文 OAI收割 PATTERN RECOGNITION, 2022, 卷号: 122, 页码: 11 作者: Yang, Jing; Yang, Xu; Zhou, Zhang-Bing; Liu, Zhi-Yong \| 收藏 \| 浏览/下载：79/0 \| 提交时间：2021/11/04 Graph matching Fast normalized cut Discrete constraint Multiplicative update
	Self-Adapting Patch Strategies for Face Recognition 期刊论文 OAI收割 INTERNATIONAL JOURNAL OF PATTERN RECOGNITION AND ARTIFICIAL INTELLIGENCE, 2020, 卷号: 34, 期号: 2, 页码: 17 作者: Li, Zhi-Ming; Li, Wen-Juan; Wang, Jun \| 收藏 \| 浏览/下载：27/0 \| 提交时间：2020/06/02 Two-dimensional discrete wavelet transform self-adapting patch strategy edge recovery local binary pattern adaptive forward-backward greedy algorithm sparse constraint
	Self-adapting Patch Strategies for Face Recognition 期刊论文 OAI收割 INTERNATIONAL JOURNAL OF PATTERN RECOGNITION AND ARTIFICIAL INTELLIGENCE, 2019, 卷号: 34, 期号: 2, 页码: 2056002-1-17 作者: Li, Zhiming; Li, Wenjuan; Wang, Jun \| 收藏 \| 浏览/下载：29/0 \| 提交时间：2020/10/16 Two-dimensional discrete wavelet transform edge recovery local binary pattern adaptive forward-backward greedy algorithm sparse constraint self-adapting patch strategy
	Engineering molecular dynamics simulation in chemical engineering 期刊论文 OAI收割 Chemical Engineering Science, 2015, 页码: 200-216 Xu, J.; Li, X. X.; Hou, C. F.; Wang, L. M.; Zhou, G. Z.; Ge, W.; Li, J. H. 收藏 \| 浏览/下载：30/0 \| 提交时间：2015/04/01 Engineering MD simulation Chemical processes Meso-scale Multiscale EMMS paradigm Particle methods SMOOTHED PARTICLE HYDRODYNAMICS FORCE-DISPLACEMENT MODEL FINITE/DISCRETE ELEMENT SIMULATION LINEAR CONSTRAINT SOLVER SHOT PEENING PROCESSES COAL PYROLYSIS STABILITY CONDITION MULTISCALE METHOD INTERACTION LAWS FLUIDIZED-BEDS
	An efficient discrete particle swarm algorithm for task assignment problems (EI CONFERENCE) 会议论文 OAI收割 2009 IEEE International Conference on Granular Computing, GRC 2009, August 17, 2009 - August 19, 2009, Nanchang, China 作者: Wang C. 收藏 \| 浏览/下载：14/0 \| 提交时间：2013/03/25 Task Assignment Problems (TAPs) in distributed computer system are general NP-hard and usually modeled as integer programming discrete problems. Many algorithms are proposed to resolve those problems. Discrete particle swarm algorithm (DPS) is a newly developed method to solve constraint satisfaction problem (CSP) which has advantage on search capacity and can find more solutions. We proposed an improved DPS to solve TAP in this paper. DPS has a special operator namely coefficient multiplying speed which is designed for CSP but does not exist in other discrete problems. Thus we redefined a coefficient multiplying speed operator with probability selection. We analyzed the speed and position updating formula then we derived a refined position updating formula. Several experiments are carried out to test our DPS. Experimental results show that our algorithm has more efficient search capacity higher success rate less running time and more robust.
	A comparative study of discrete differential evolution on binary constraint satisfaction problems (EI CONFERENCE) 会议论文 OAI收割 2008 IEEE Congress on Evolutionary Computation, CEC 2008, June 1, 2008 - June 6, 2008, Hong Kong, China Yang Q. 收藏 \| 浏览/下载：65/0 \| 提交时间：2013/03/25 There are some variants and applications of the discretization of differential evolution. Performances of discrete differential evolution algorithms on random binary constraint satisfaction problem are studied in this paper and a novel discrete differential evolution algorithm based on exchanging elements is proposed. We compare the proposed discrete differential evolution evolutionary algorithms and discrete particle swarm optimization on random binary constraint satisfaction problems. Experimental results indicate though the proposed algorithm is simpler it is competitive with other evolutionary algorithms solving constraint satisfaction problems. 2008 IEEE.