Structure of Salp Swarm Algorithm
Author:
Publisher
Springer Nature Singapore
Link
https://link.springer.com/content/pdf/10.1007/978-981-19-9733-4_7
Reference24 articles.
1. Abusnaina, A. A., Ahmad, S., Jarrar, R., & Mafarja, M. (2018). Training neural networks using salp swarm algorithm for pattern classification. ACM International Conference Proceeding Series. https://doi.org/10.1145/3231053.3231070
2. Aljarah, I., Habib, M., Faris, H., Al-Madi, N., Heidari, A. A., Mafarja, M., Elaziz, M. A., & Mirjalili, S. (2020). A dynamic locality multiobjective salp swarm algorithm for feature selection. Computers and Industrial Engineering. https://doi.org/10.1016/j.cie.2020.106628
3. Bairathi, D., & Gopalani, D. (2019). Salp swarm algorithm (SSA) for-training feed-forward neural networks. Advances in Intelligent Systems and Computing. https://doi.org/10.1007/978-981-13-1592-3_41
4. Braik, M., Sheta, A., Turabieh, H., & Alhiary, H. (2021). A novel lifetime scheme for enhancing the convergence performance of salp swarm algorithm. Soft Computing. https://doi.org/10.1007/s00500-020-05130-0
5. Ehteram, M., Panahi, F., Ahmed, A. N., Huang, Y. F., Kumar, P., & Elshafie, A. (2022). Predicting evaporation with optimized artificial neural network using multiobjective salp swarm algorithm. Environmental Science and Pollution Research. https://doi.org/10.1007/s11356-021-16301-3
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