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Results for Particle swarm optimization

Publications & Outputs

  1. A Multi-Swarm PSO Approach to Large-Scale Task Scheduling in a Sustainable Supply Chain Datacenter

    Liu, Q., Zeng, L., Bilal, M., Song, H., Liu, X., Zhang, Y. & Cao, X., 1/12/2023, In: IEEE Transactions on Green Communications and Networking. 7, 4, p. 1667 - 1677

    Research output: Contribution to Journal/Magazine › Journal article › peer-review

  2. Reliability-aware swarm based multi-objective optimization for controller placement in distributed SDN architecture

    Ibrahim, A. A. Z., Hashim, F., Sali, A., Noordin, N. K., Navaie, K. & Fadul, S. M. E., 20/11/2023, (Accepted/In press) In: Digital Communications and Networks.

    Research output: Contribution to Journal/Magazine › Journal article › peer-review

  3. Training simple recurrent deep artificial neural network for forecasting using particle swarm optimization

    Bas, E., Egrioglu, E. & Kolemen, E., 22/06/2021, (E-pub ahead of print) In: Granular Computing. 10 p.

    Research output: Contribution to Journal/Magazine › Journal article › peer-review

  4. A new fuzzy time series method based on an ARMA-type recurrent Pi-Sigma artificial neural network

    Kocak, C., Dalar, A. Z., Yolcu, O. C., Bas, E. & Egrioglu, E., 1/06/2020, In: Soft Computing. 24, 11, p. 8243-8252 10 p.

    Research output: Contribution to Journal/Magazine › Journal article › peer-review

  5. AR–ARCH Type Artificial Neural Network for Forecasting

    Corba, B. S., Egrioglu, E. & Dalar, A. Z., 1/02/2020, In: Neural Processing Letters. 51, p. 819–836 18 p.

    Research output: Contribution to Journal/Magazine › Journal article › peer-review

  6. Intuitionistic time series fuzzy inference system

    Egrioglu, E., Bas, E., Yolcu, O. C. & Yolcu, U., 30/06/2019, In: Engineering Applications of Artificial Intelligence. 82, p. 175-183 9 p.

    Research output: Contribution to Journal/Magazine › Journal article › peer-review

  7. Median-Pi artificial neural network for forecasting

    Egrioglu, E., Yolcu, U., Bas, E. & Dalar, A. Z., 18/01/2019, In: Neural Computing and Applications. 31, 1, p. 307-316 10 p.

    Research output: Contribution to Journal/Magazine › Journal article › peer-review

  8. High order fuzzy time series method based on pi-sigma neural network

    Bas, E., Grosan, C., Egrioglu, E. & Yolcu, U., 1/06/2018, In: Engineering Applications of Artificial Intelligence. 72, p. 350-356 7 p.

    Research output: Contribution to Journal/Magazine › Journal article › peer-review

  9. A new hybrid method for time series forecasting: AR–ANFIS

    Sarıca, B., Eğrioğlu, E. & Aşıkgil, B., 1/02/2018, In: Neural Computing and Applications. 29, 3, p. 749-760 12 p.

    Research output: Contribution to Journal/Magazine › Journal article › peer-review

  10. Recurrent type-1 fuzzy functions approach for time series forecasting

    Tak, N., Evren, A. A., Tez, M. & Egrioglu, E., 1/01/2018, In: Applied Intelligence. 48, 1, p. 68-77 10 p.

    Research output: Contribution to Journal/Magazine › Journal article › peer-review

  11. Particle swarm optimization based Liu-type estimator

    Inan, D., Egrioglu, E., Sarica, B., Askin, O. E. & Tez, M., 17/11/2017, In: Communications in Statistics - Theory and Methods. 46, 22, p. 11358-11369 12 p.

    Research output: Contribution to Journal/Magazine › Journal article › peer-review

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