Cultured Artificial Fish Swarm Algorithm: An Experimental Evaluation

被引：0
|
作者：
Imam, Maryam Lami [1 ]
Adebiyi, Busayo H. [2 ]
Bello-Salau, Habeeb [2 ]
Olarinoye, Gbenga A. [3 ]
Momoh, Muyideen O. [2 ]
机构：
[1] Univ Jos, Dept Elect & Elect Engn, Jos, Nigeria
[2] Ahmadu Bello Univ, Dept Comp Engn, Zaria, Nigeria
[3] Ahmadu Bello Univ, Dept Elect Engn, Zaria, Nigeria
来源：
2019 2ND INTERNATIONAL CONFERENCE OF THE IEEE NIGERIA COMPUTER CHAPTER (NIGERIACOMPUTCONF) | 2019年
关键词：
Artificial Fish Swarm Algorithm; Inertia Weight; Culture Algorithm; Test Functions; OPTIMIZATION;
D O I：
10.1109/nigeriacomputconf45974.2019.8949657
中图分类号：
TP39 [计算机的应用];
学科分类号：
081203 ; 0835 ;
摘要：
In this work, a Weighted Cultural Artificial Fish Swarm Algorithm (wCAFSA) which is an amendment of standard artificial fish swarm algorithm (AFSA) is proposed. This algorithm can adaptively select its parameters at every generation in order to reduce the ease at which standard AFSA falls into local optimal We first introduce inertial weight to adaptively determine visual distance and step size of AFSA thereafter, the Situational and Normative knowledge inherent in cultural algorithm are used to develop new variants of weighted cultural AFSA (wCAFSA Ns, wCAFSA sd, wCAFSA Ns+Sd and wCAFSA Ns+Nd). A collection of sixteen (16) optimization benchmark functions are used to test the performance of the algorithms. The simulation results disclosed that all the new variants of the wCAFSA outclassed the AFSA.
引用
收藏
页码：198 / +
页数：7
相关论文
共 50 条
  • [31] A Novel WSNs Localization Algorithm Based on Artificial Fish Swarm Algorithm
    Yang, Xiaoying
    Zhang, Wanli
    Song, Qixiang
    INTERNATIONAL JOURNAL OF ONLINE ENGINEERING, 2016, 12 (01) : 64 - 68
  • [32] 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
  • [33] Hybrid Optimization Algorithm lased on Mean Particle Swarm and Artificial Fish Swarm
    Zhou, Yongquan
    Huang, Xingshou
    Yang, Yan
    Wu, Jinzhao
    INFORMATION-AN INTERNATIONAL INTERDISCIPLINARY JOURNAL, 2012, 15 (02): : 763 - 777
  • [34] Quantum Behaved Particle Swarm Optimization Algorithm Based on Artificial Fish Swarm
    Yumin, Dong
    Li, Zhao
    MATHEMATICAL PROBLEMS IN ENGINEERING, 2014, 2014
  • [35] 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
  • [36] Spread spectrum code estimation by artificial fish swarm algorithm
    Jiang, Mingyan
    Wang, Yong
    Rubio, Francisco
    Yuan, Dongfeng
    2007 IEEE INTERNATIONAL SYMPOSIUM ON INTELLIGENT SIGNAL PROCESSING, CONFERENCE PROCEEDINGS BOOK, 2007, : 211 - +
  • [37] Community Detection Algorithm Based on Artificial Fish Swarm Optimization
    Hassan, Eslam Ali
    Hafez, Ahmed Ibrahem
    Hassanien, Aboul Ella
    Fahmy, Aly A.
    INTELLIGENT SYSTEMS'2014, VOL 2: TOOLS, ARCHITECTURES, SYSTEMS, APPLICATIONS, 2015, 323 : 509 - 521
  • [38] 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
  • [39] Niche Artificial Fish Swarm Algorithm Based on Quantum Theory
    Zhu, Kongcun
    Jiang, Mingyan
    Cheng, Yongming
    2010 IEEE 10TH INTERNATIONAL CONFERENCE ON SIGNAL PROCESSING PROCEEDINGS (ICSP2010), VOLS I-III, 2010, : 1425 - 1428
  • [40] An adaptive artificial fish swarm algorithm with elimination and clone mechanism
    Zhenghua, Yao
    Zihui, Ren
    Computer Modelling and New Technologies, 2014, 18 (12): : 110 - 116
12345