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RISS 인기검색어
- 검색키워드
- 저자 : Jianwu Dang (검색결과 4 건)
- 무료
- 기관 내 무료
- 유료
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Analysis and Improvement of the Bacterial Foraging Optimization Algorithm
Jun Li,Jianwu Dang,Feng Bu,Jiansheng Wang 한국정보과학회 2014 Journal of Computing Science and Engineering Vol.8 No.1
The Bacterial Foraging Optimization Algorithm is a swarm intelligence optimization algorithm. This paper first analyzes the chemotaxis, as well as elimination and dispersal operation, based on the basic Bacterial Foraging Optimization Algorithm. The elimination and dispersal operation makes a bacterium which has found or nearly found an optimal position escape away from that position, which greatly affects the convergence speed of the algorithm. In order to avoid this escape, the sphere of action of the elimination and dispersal operation can be altered in accordance with the generations of evolution. Secondly, we put forward an algorithm of an adaptive adjustment of step length we called improved bacterial foraging optimization (IBFO) after making a detailed analysis of the impacts of the step length on the efficiency and accuracy of the algorithm, based on chemotaxis operation. The classic test functions show that the convergence speed and accuracy of the IBFO algorithm is much better than the original algorithm.
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Xin Zhang,Jianwu Dang,Yangping Wang 보안공학연구지원센터 2015 International Journal of Hybrid Information Techno Vol.8 No.9
Accelerator has been widely applied to high energy, low energy physics, Medical environmental and military fields, etc. The magnet power supply is one of the most important parts of the accelerator. While the magnet power supply of accelerator is taken as the control object, and the design of LQR controller of the magnet power supply based on PSO has been proposed. At the beginning, the state-space model of the magnet power supply has been established by modern control theories. Then, the PSO (Particle Swarm Optimization) algorithm has been used for the weight matrices optimization of LQR controller in order to ensure that the magnet power supply can provide a magnetic field quickly which the accelerator required. The experimental results indicate that the method that proposed in the paper can meet the requirements of fast output response of the system and each control index of the LQR controller is obviously superior to that by the traditional method.
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Analysis and Improvement of the Bacterial Foraging Optimization Algorithm
Li, Jun,Dang, Jianwu,Bu, Feng,Wang, Jiansheng Korean Institute of Information Scientists and Eng 2014 Journal of Computing Science and Engineering Vol.8 No.1
The Bacterial Foraging Optimization Algorithm is a swarm intelligence optimization algorithm. This paper first analyzes the chemotaxis, as well as elimination and dispersal operation, based on the basic Bacterial Foraging Optimization Algorithm. The elimination and dispersal operation makes a bacterium which has found or nearly found an optimal position escape away from that position, which greatly affects the convergence speed of the algorithm. In order to avoid this escape, the sphere of action of the elimination and dispersal operation can be altered in accordance with the generations of evolution. Secondly, we put forward an algorithm of an adaptive adjustment of step length we called improved bacterial foraging optimization (IBFO) after making a detailed analysis of the impacts of the step length on the efficiency and accuracy of the algorithm, based on chemotaxis operation. The classic test functions show that the convergence speed and accuracy of the IBFO algorithm is much better than the original algorithm.
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Research on Background Extraction of Dynamic Video
Jun Li,Jianwu Dang,Jiansheng Wang 보안공학연구지원센터 2015 International Journal of Hybrid Information Techno Vol.8 No.10
As for heavy traffic, road congestion and the hard extraction of vehicles in dynamic video, an improved method of dynamic video background updating is proposed. By using frame-to-frame differences and mask technology, the hole of difference image is eliminated, then extracts the reliably initial background. The image is segmented by using double threshold based on the combination of Bacterial Foraging Optimization Algorithm and Otsu Algorithm to improve the effect and reliability of background updating. Experiments shows that it is an effective way that is good in speed and effective in background extraction, and provides a good foundation for further study of the vehicle tracking.
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