Name
Title | ||
|---|---|---|
An adaptive hydrologic cycle optimization algorithm for numerical optimization and data clustering |
Abstract | ||
|---|---|---|
The circulation and convergence of water in the hydrologic cycle process inspired us to design a new optimization algorithm, the Hydrologic Cycle Optimization (HCO) algorithm. In this study, a comprehensive demonstration of the HCO was presented. First, a simplified model of the hydrological cycle phenomenon was established. Then, the framework of HCO and its operators were discussed and verified in detail. Several experiments were done to test the optimization ability of the HCO algorithm. In the first experiment, the parameter settings were tested, and an adaptive version of the algorithm was proposed. Then the HCO was tested on 20 numeric optimization benchmark functions and eight data clustering sets, respectively, and compared with other algorithms. The experimental results showed that the HCO is superior to the compared algorithms, indicating that it is a competitive approach for numerical and engineering optimization problems. |
Year | DOI | Venue |
|---|---|---|
2022 | 10.1002/int.22836 | INTERNATIONAL JOURNAL OF INTELLIGENT SYSTEMS |
Keywords | DocType | Volume |
computational intelligence, evolutionary computation, hydrologic cycle optimization, optimization algorithm, swarm intelligence | Journal | 37 |
Issue | ISSN | Citations |
9 | 0884-8173 | 0 |
PageRank | References | Authors |
0.34 | 0 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Xiaohui Yan | 1 | 0 | 0.34 |
| Ben Niu | 2 | 235 | 44.62 |
| Yujuan Chai | 3 | 0 | 0.34 |
| Zhicong Zhang | 4 | 0 | 0.34 |
| Liangwei Zhang | 5 | 0 | 0.34 |