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RISS 인기검색어
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- 저자 : Yongfeng Cui (검색결과 4 건)
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RBF Adaptive Control Strategy Based on Sub-Block Approximation Algorithm for Binocular Vision Robot
Yongfeng Cui,Chong Tian 보안공학연구지원센터 2016 International Journal of Multimedia and Ubiquitous Vol.11 No.8
Intelligent robot not only can realize reservation on conduct and actions, but also can be understand the characteristics of the unknown environment and adapt to changes in the environment through their own "sensory system", robots get outside information mainly by vision, this paper take the joint robot of binocular robot vision system as control plant, pointing on the problem of the uncertainties that existed in the dynamic model of binocular vision robot may cause instability. This paper has proposed a sliding model control scheme with RBF neural network adaptive control strategy based on sub-block approximation algorithm, in this control method, sliding model control was used to control trajectory of the joints of robot, and utilize the RBF neural network to approximate the each uncertain in the dynamic model of robot. The simulation results show that compared with the RBF neural network adaptive control strategy based on integral approximation for uncertainness, the proposed control method has features with good position tracking.
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Enterprise Computer Network Reliability Analysis
Yongfeng Cui,Wei Liu,Ya Li 보안공학연구지원센터 2015 International Journal of Multimedia and Ubiquitous Vol.10 No.1
This paper considers the multi-protocol label switching enterprise computer network routing optimization problem, in the network reliability constraints, by selecting the optimal work and alternate paths, and carries on the bandwidth allocation; network total construction cost is minimal. Due to the total construction cost and network reliability is related to choice of the length of the path, the optimal route network design problem can be decoupled into two sub-problems: cost and reliability related issues, among them, the cost of related sub problem study, Sohn et al. For reliability related problems, reduce the search space understanding, this chapter will work best and standby path search space from a hyper plane reduce to the hyper plane line; Then, reliability related algorithm is proposed to solve the problem. Because of the cost and reliability related sub-problem solutions are obtained based on the same search criterion, so the original problem of optimal work and backup path of solution set is by comparing the two sub problems solution to work out. Finally, related algorithm provides a numerical example to verify the reliability and the validity of the global network routing design method.
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Application of Improved BP Neural Network with Correlation Rules in Network Intrusion Detection
Yongfeng Cui,Xiangqian Li Ma,Zhijie Liu 보안공학연구지원센터 2016 International Journal of Security and Its Applicat Vol.10 No.4
To detect various network attacks in real time, this paper developed a network intrusion detection system based on artificial neural network. This paper first introduced the recent development of neural network, BP algorithm and structure of a simple perceptron. Then, this paper developed an improved BP neural network algorithm to detect anomaly network traffic with adjusted correlation rules. Finally, the network intrusion system in this paper was tested in a real network situation; the improved BP algorithm neural network with adjusted correlation rules shows a reduction in total error and increment in alarm rate compared to the traditional basic BP algorithm model.
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Research and Application of Intelligent Recommendation System Based on Big Data Technology
Yongfeng Cui,Yuankun Ma,Zhongyuan Zhao 보안공학연구지원센터 2016 International Journal of Database Theory and Appli Vol.9 No.8
With the rapid development of information technology and the Internet, people entered the era of information overload. Recommended system is an effective tool to solve the problem of information overload, it is based on the historical behavior of users and other records of interest to the user modeling, and then use the model to create user interest personalized recommendation, the interested user information, products. Online Intelligence is a new research direction, which integrates the latest achievements of artificial intelligence and information technology, greatly emphasizes on the Internet means intelligent application of data mining technology in the online intelligence research has a very important position. This paper presents a project-based collaborative filtering algorithm hierarchical similarity. Users to take advantage of some of the projects marked tags and project categories were automatically extended, to establish a hierarchy of all projects, and then use similar items tag hierarchy established between computing projects. Experimental results show that compared with traditional collaborative filtering algorithm, the ability of collaborative filtering algorithm based on similarity of item level can significantly improve the recommendation system to handle large data presented in this paper.
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