An Improved Artificial Fish Swarm Algorithm and Application

被引:0
|
作者
Luan, Xinyuan [1 ]
Jin, Biyao [1 ]
Liu, Tingzhang [1 ]
Zhang, Yingqi [1 ]
机构
[1] Shanghai Univ, Sch Mechatron Engn & Automat, Shanghai Key Lab Power Stn Automat Technol, Shanghai 200072, Peoples R China
来源
COMPUTATIONAL INTELLIGENCE, NETWORKED SYSTEMS AND THEIR APPLICATIONS | 2014年 / 462卷
关键词
LED; AFSA; HJ; color mixing; optimization;
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
An improved Artificial Fish Swarm Algorithm (AFSA) based on Hooke-Jeeves (HJ) algorithm is proposed and improved AFSA is applied to design lamps of changeable color temperature and high luminous efficacy in this paper. The disadvantage of AFSA stochastic moving without a definite purpose is improved by HJ algorithm, owing to HJ's great ability of local searching. Accuracy of solution is improved by the adaptive weight. The improved AFSA is verified through an example of how to search for the most luminous efficacy of LED mixing color. The white, red, green and blue LEDs are chosen to design LED lamp samples. LED proportions of 5000K color temperature among those LEDs are optimized by AFSA and new AFSA in the Matlab. The obtained results indicate that improved AFSA is faster and higher accuracy. After LED lamps are tested by integrating sphere, the results show that the difference between the actual value and simulation calculation value is tiny, the new AFSA is effective. The improved AFSA provides a new efficient calculation method of LED proportions. Compared with the traditional manual calculation LED proportions, new method not only saves a significant amount of time, but also achieves higher luminous efficacy for lamps. All this shows that the new method is effective and has high practical value.
引用
收藏
页码:99 / 110
页数:12
相关论文
共 50 条
  • [21] The routing optimization based on improved artificial fish swarm algorithm
    Shan, Xiaojuan
    Jiang, Mingyan
    Li, Jingpeng
    WCICA 2006: SIXTH WORLD CONGRESS ON INTELLIGENT CONTROL AND AUTOMATION, VOLS 1-12, CONFERENCE PROCEEDINGS, 2006, : 3658 - +
  • [22] An improved artificial fish swarm algorithm for traffic signal control
    Lu B.
    Wang Q.
    Wang Y.
    International Journal of Simulation and Process Modelling, 2019, 14 (06) : 488 - 499
  • [23] An Improved Artificial Fish Swarm Algorithm for Cutting Stock Problem
    Song, Chuyi
    Jiang, Jingqing
    Bai, Siqin
    Bao, Lanying
    2013 NINTH INTERNATIONAL CONFERENCE ON NATURAL COMPUTATION (ICNC), 2013, : 501 - 505
  • [24] An improved artificial fish swarm algorithm optimized by particle swarm optimization algorithm with extended memory
    Duan, Qichang
    Mao, Mingxuan
    Duan, Pan
    Hu, Bei
    KYBERNETES, 2016, 45 (02) : 210 - 222
  • [25] An improved discrete optimization algorithm based on artificial fish swarm and its application for attribute reduction
    Ni, Zhiwei
    Zhu, Xuhui
    Ni, Liping
    Cheng, Meiying
    Wang, Yiling
    Journal of Information and Computational Science, 2015, 12 (06): : 2143 - 2154
  • [26] An Improved DV-Hop Algorithm Based on Artificial Fish Swarm Algorithm
    Yang, Xiaoying
    Rui, Kai
    IAEDS15: INTERNATIONAL CONFERENCE IN APPLIED ENGINEERING AND MANAGEMENT, 2015, 46 : 223 - 228
  • [27] Application of the Artificial Fish Swarm Algorithm to Well Trajectory Optimization
    Sun, Tengfei
    Zhang, Hui
    Gao, Deli
    Liu, Shujie
    Cao, Yanfeng
    CHEMISTRY AND TECHNOLOGY OF FUELS AND OILS, 2019, 55 (02) : 213 - 218
  • [28] The Application of Artificial Fish Swarm Algorithm in the Optimization of Well Trajectory
    Sun Tengfei
    Qian Feng
    Kong Xiangji
    ELECTRONIC JOURNAL OF GEOTECHNICAL ENGINEERING, 2016, 21 (15): : 4937 - 4944
  • [29] The application of artificial fish swarm algorithm in the optimization of drag and torque
    Sun, Tengfei
    Gao, Deli
    Liu, Shujie
    Cao, Yanfeng
    Zhang, Hui
    Electronic Journal of Geotechnical Engineering, 2014, 19 (0X): : 3837 - 3845
  • [30] Application of the Artificial Fish Swarm Algorithm to Well Trajectory Optimization
    Tengfei Sun
    Hui Zhang
    Deli Gao
    Shujie Liu
    Yanfeng Cao
    Chemistry and Technology of Fuels and Oils, 2019, 55 : 213 - 218