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Search Results: 1 - 10 of 113390 matches for " CHEN Guo-long "
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Fuzzy Self-Adapted Particle Swarm Optimization Algorithm for Traveling Salesman Problems

GUO Wen-Zhong,CHEN Guo-Long,

计算机科学 , 2006,
Abstract: The Particle swarm optimization(PSO)is an algorithm for finding optimal regions of complex search spaces through the interaction of individuals in a population of particles. The setting of inertia weight plays a key role in the performance of PSO, so many presented improved PSO algorithms based inertia weight were advanced. Based on fuzzy technology, a new fuzzy self-adapted model of inertia weight and corresponding PSO are proposed in the paper, then this paper proposes its application to traveling salesman problems(TSP). In the new PSO, different inertia weights are used in updating the particle swarm in a same generation. The experiments show that the new PSO algorithm can achieve good results. Compared with the linearly decreasing inertia weight PSO, the new algorithm also improves the performance of PSO and speeds up the velocity of the PSO convergence.
The Performance Analysis of Wu-Manber Algorithm and its Improvement

CHEN Yu,CHEN Guo-Long,

计算机科学 , 2006,
Abstract: In the field of pattern matching, the multiple pattern matching algorithms attract more and more attentions. This paper firstly introduces some famous multiple pattern matching algorithms and puts emphasis on the basic idea and the implementation principle of the Wu-Manber algorithm which is the most efficient in practice. Then, an improvement to the Wu Manber algorithm is provided to solve the problem of performance falling when the patterns are very Short, At last, the experiment data show that the performance of the improved Wu Manber algorithm is much better than the traditional Wu-Manber algorithm.
Linear Combination Forecasting Model and its Application

GAN Jian-Sheng,CHEN Guo-Long,

计算机科学 , 2006,
Abstract: The key of forecasting is modeling,but every kind of model has its own advantages.A more efficient model can be obtained by a linear combination of some models.In this paper,Fujian urban household's Engle coefficient is forecasted by linear regression model,gray system model,genetic algorithms back propagation network (GABP) model and linear combination model.It is found that the best one is the linear combination model.
Automatic image annotation refinement based on keyword co-occurrence and WordNet

KE Xiao,LI Dong-yan,CHEN Guo-long,
柯 逍

计算机应用研究 , 2012,
Abstract: Image automatic annotation is a significant and challenging problem in pattern recognition and computer vision areas. At present, most existing image annotation models are influenced by semantic gap problem. This paper proposed a new image automatic annotation refinement method based on keyword co-occurrence to overcome above problem, which used the correlations between keywords in dataset to improve image annotation result. However, above method did not reflect the generalized knowledge of people and easy influenced by the size of dataset. Aiming at above problem, it proposed a new image automatic annotation refinement method based on semantic similarity to overcome above problem. This method used semantic dictionary WordNet to calculate the correlations between keywords and improve the image annotation results. Experimental results conduct on Corel 5K datasets verify the effectiveness of proposed image annotation method. The proposed automatic image annotation model improves the annotation results on all evaluation methods.
Research and Application of Correlation-based Genetic Algorithm

FANG Xiao-tong,CHEN Guo-long,YE Wen-hui,

计算机应用研究 , 2005,
Abstract: This paper analyses research status in quo of correlation-based data mining technology, gives the definition of correlation rule and advances the correlation-based fitness function. Then this paper makes a new genetic algorithm which is based on correlation rule, and apples it to the credit card analysis system. An example of feature selection is performed, the result shows that this algorithm has good predictive ability.
Improved negative selection algorithm for network anomaly detection on high-dimensional data

GUO Wen-zhong,CHEN Guo-long,CHEN Qing-liang,

计算机应用 , 2009,
Abstract: Negative Selection(NS) algorithm of artificial immunology has been successfully applied to anomaly detection on some low-dimension data,but the performance becomes unfavorable on high-dimension data.Real-valued negative selection algorithm with variable-sized detectors(VRNS) was applied to network intrusion detection and a variation of it(IVRNS) was proposed to improve the performance on high-dimension data.In the improved algorithm,the detectors were used to control the coverage of them according to the ov...
Feature Subset Selection Based on Particle Swarm Optimization Algorithm and Relevance Analysis

GUO Wen-Zhong,CHEN Guo-Long,CHEN Qing-Liang,YU Lun,

计算机科学 , 2008,
Abstract: Feature selection is one of the important problems in the pattern recognition and data mining areas.The new feature subset selection method based on discrete binary version of particle swarm optimization(PSO)algorithm and relevance analysis is proposed.This new method employs the filter mode feature selection algorithm,which focuses on the correlation among the features of the network traffic data and employs the discrete particle swarm algorithm to find an optimized feature set.Experiments in 1999 KDD Cup Data confirm the effectiveness of the proposed strategy.
An Improved Algorithm to Solve the Multi-Criteria Minimum Spanning Tree Problem

CHEN Guo-Long,GUO Wen-Zhong,TU Xue-Zhu,CHEN Huo-Wang,

软件学报 , 2006,
Abstract: The multi-criteria minimum spanning tree (mc-MST) problem is a typical NP-hard problem. An algorithm to enumerate the set of Pareto optimal spanning trees on some mc-MST instances was put forward by Zhou and Gen, but it does not guarantee returning all the Pareto optimal solutions. To settle this problem, an improved algorithm is developed and also proved to be able to find all the true Pareto optimal solutions in this paper. The new algorithm adds some conditions in the elimination of subtrees. Simulation results show that the new algorithm can find all the Pareto optimal solutions and also show that the new algorithm has potential usage in practice.
Design of IPSec Gateway Based on IXP2400 Network Processor
基于IXP2400网络处理器的IPSec VPN网关设计

LIU Yan-hua CHEN Guo-long GUO Wen-zhong,

计算机科学 , 2008,
Abstract: VPN gateway is important in high-speed network security.To resolve the problem that is low-speed or low-flexibility based on X86 CPU and ASIC,proposed high-speed IPSec VPN design based on IXP2400.The simulation environment experiment proved that the new VPN gateway is high-speed over 1.0Gbps.And it supplies a new approach to design high-speed VPN gateway system.
Research of Network Information Monitor Technology

CHEN Guo-Long CHEN Huo-Wang KANG Zhong-Sheng,

计算机科学 , 2003,
Abstract: As a sign of information age, Internet offers millions of information and makes the people's work easy. However, when the enterprise gets the information and communicates smoothly, it is at the risk that the interior technologic secret and the commerce secret is betrayed to the rival through the network. So it is necessary to aduit the information of the network. Network information aduit is the first step of network information aduit. This thesis provides a method of the network information monitor, and gives an effective network packet filters technology named BPF aiming at dealing with the large number of data on the network.
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