Abstract
A new optimization algorithm (named DIMO) based on diversity enhanced Ion Motion Optimization (IMO) is proposed. Diversity learning strategy and random perturbations are applied to improve IMO by modifying its individual evolutionary information. A set of selected benchmark functions and an estimation localization in Wireless sensor network (WSN) are used to test the performance of the proposed algorithm. The experimental results compared with the others algorithms in the literature shows that the proposed approach are superior to the other algorithms in optimization accuracy, convergence speed, and robustness.
| Original language | English |
|---|---|
| Pages (from-to) | 221-229 |
| Number of pages | 9 |
| Journal | Journal of Information Hiding and Multimedia Signal Processing |
| Volume | 10 |
| Issue number | 1 |
| Publication status | Published - Jan 2019 |
Keywords
- DIMO
- Meta-heuristic
- Wireless sensor network
- Global Positioning System
- GPS
- WSN
- Ion Motion
- Optimization
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Pan, J. S., Nguyen, T. T., Chu, S. C., Dao, T. K., & Ngo, T. G. (2019). Diversity enhanced ion motion optimization for localization in wireless sensor network. Journal of Information Hiding and Multimedia Signal Processing, 10(1), 221-229. http://bit.kuas.edu.tw/~jihmsp/2019/vol1/JIH-MSP-2019-01-24.pdf