Human learning principles inspired particle swarm optimization algorithms
These days, the nature of global optimization problems, especially for engineering systems has become extremely complex. For these types of problems, nature inspired search based algorithms are providing much better solutions compared with other classical optimization methods. Among them, the Par...
Saved in:
主要作者: | Muhammad Rizwan Tanweer |
---|---|
其他作者: | Suresh Sundaram |
格式: | Theses and Dissertations |
語言: | English |
出版: |
2017
|
主題: | |
在線閱讀: | http://hdl.handle.net/10356/72198 |
標簽: |
添加標簽
沒有標簽, 成為第一個標記此記錄!
|
相似書籍
-
Genetic algorithm search space splicing particle swarm optimization as general-purpose optimizer
由: Hao Li, et al.
出版: (2018) -
A hybrid particle swarm optimization with cooperative method for multi-object tracking
由: Zhang, Zheng, et al.
出版: (2013) -
Dynamic multi-swarm particle swarm optimization for multi-objective optimization problems
由: Niu, B., et al.
出版: (2013) -
A dynamic neighborhood learning based particle swarm optimizer for global numerical optimization
由: Nasir, Md., et al.
出版: (2013) -
Genetic algorithms for swarm parameter tuning
由: Chee, Glenn Jun Yuan
出版: (2019)