Application of Ant Colony Algorithm in Power Grid Data Management

Author:

Zhang Wenjia,Han Xiao,Cai Chao,Wang Quanquan,Zang Zhibin,Shi Zhongmin,Yao Shuo,Dominguez Martha

Publisher

Springer Nature Singapore

Reference10 articles.

1. Dewangan, B., Jain, A., Shukla, R., et al.: An ensemble of bacterial foraging, genetic, ant colony and particle swarm approach EB-GAP: a load balancing approach in cloud computing. Recent Adv. Comput. Sci. Commun. 5, 15 (2022)

2. Meng, Xiaoling, Zhu, Xijing, Zhao, Jing: Obstacle avoidance path planning using the elite ant colony algorithm for parameter optimization of unmanned aerial vehicles. Arabian J. Sci. Eng. 48(2), 2261–2275 (2022). https://doi.org/10.1007/s13369-022-07204-7

3. Zhang, X., Zhan, Z.H., Fang, W., et al.: Multi population ant colony system with knowledge based local searches for multiobjective supply chain configuration. IEEE Trans. Evolution. Comput. 99, 1 (2021)

4. Liu, D., Li, C.Y., Jiang, Z., et al.: Integrated power grid management system based on micro service. In: 2020 Eighth International Conference on Advanced Cloud and Big Data (CBD) (2020)

5. Hu, Z.: Power grid planning and dynamic intelligent management system construction based on operation simulation. J. Phys. Conf. Ser. 2143(1), 012015 (2021)

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