Inferring structure and parameters of dynamic system models simultaneously using swarm intelligence approaches

Usman, M., Pang, W., Coghill, G.

Memetic Computing, vol. 12, pp. 267-282

Contributions to Journals: Articles

Digital Object Identifier

https://doi.org/10.1007/s12293-020-00306-5

Open Access

http://aura.abdn.ac.uk/bitstream/2164/14939/1/Usman_etal_MC_InferringStructureAndParameter_VOR.pdf

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Self-adaptive parameter and strategy based particle swarm optimization for large-scale feature selection problems with multiple classifiers

Xue, Y., Tang, T., Pang, W., Liu, A. X.

Applied Soft Computing, vol. 88, 106031

Contributions to Journals: Articles

Digital Object Identifier

https://doi.org/10.1016/j.asoc.2019.106031

Open Access

http://aura.abdn.ac.uk/bitstream/2164/15557/1/Xue_etal_ApplSofCom_AAM.pdf

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DeepSwarm: Optimising Convolutional Neural Networks using Swarm Intelligence

Byla, E., Pang, W.

Advances in Computational Intelligence Systems. Ju, Z., Yang, L., Yang, C., Gegov, A., Zhou, D. (eds.). Cham: Springer pp. 119-130, 12 pages.

Chapters in Books, Reports and Conference Proceedings: Conference Proceedings

Digital Object Identifier

https://doi.org/10.1007/978-3-030-29933-0_10

Open Access

http://aura.abdn.ac.uk/bitstream/2164/15034/1/Byla_Pang_DeepSwarm_Optimising_Convolutional_AAM.pdf

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Swarm Inspired Approaches for K-prototypes clustering

Albalawi, H., Pang, W., Coghill, G. M.

Advances in Computational Intelligence Systems. Ju, Z., Yang, L., Yang, C., Gegov, A., Zhou, D. (eds.). Cham: Springer pp. 201-209, 9 pages.

Chapters in Books, Reports and Conference Proceedings: Conference Proceedings

Digital Object Identifier

https://doi.org/10.1007/978-3-030-29933-0_17

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Case-based reasoning of a deep learning network for prediction of early stage of oesophageal cancer

Gao, X., Braden, B., Zhang, L., Taylor, S., Pang, W., Pettdis, M.

Proceedings of the 24th UK Symposium on Case-Based Reasoning

Chapters in Books, Reports and Conference Proceedings: Chapters

Towards Real-Time Detection of Squamous PreCancers from Oesophageal Endoscopic Videos

Gao, X., Braden, B., Taylor, S., Pang, W.

Contributions to Conferences: Papers

Open Access

http://aura.abdn.ac.uk/bitstream/2164/15234/1/conference_template_a4_1_PaperID560.pdf

Towards machine learning approaches for predicting the self-healing efficiency of materials

Wang, W., Moreau, N. G., Yuan, Y., Race, P. R., Pang, W.

Computational Materials Science, vol. 168, pp. 180-187

Contributions to Journals: Articles

Digital Object Identifier

https://doi.org/10.1016/j.commatsci.2019.05.050

Open Access

http://aura.abdn.ac.uk/bitstream/2164/12426/1/Towards_machine_learning_approaches_for_predicting_the_self_healing_efficiency_of_materials.pdf

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Explosion gravitation field algorithm with dust sampling for unconstrained optimization

Hu, X., Huang, L., Wang, Y., Pang, W.

Applied Soft Computing, vol. 81, 105500

Contributions to Journals: Articles

Digital Object Identifier

https://doi.org/10.1016/j.asoc.2019.105500

Open Access

http://aura.abdn.ac.uk/bitstream/2164/14324/1/EGFAmanuscript20190411_1_.pdf

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LatinPSO: An algorithm for simultaneously inferring structure and parameters of ordinary differential equations models

Tian, X., Pang, W., Wang, Y., Guo, K., Zhou, Y.

BioSystems, vol. 182, pp. 8-16

Contributions to Journals: Articles

Digital Object Identifier

https://doi.org/10.1016/j.biosystems.2019.05.006

Open Access

http://aura.abdn.ac.uk/bitstream/2164/14418/1/LatinPSO_FinalAccepted.pdf

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TCPModel: A Short-Term Traffic Congestion Prediction Model Based on Deep Learning

Xu, X., Gao, X., Xu, Z., Zhao, X., Pang, W., Zhou, H.

Artificial Intelligence. Knight, K., Zhang, C., Holmes, G., Zhang, M. (eds.). Singapore: Springer pp. 66-79, 14 pages.

Chapters in Books, Reports and Conference Proceedings: Conference Proceedings

Digital Object Identifier

https://doi.org/10.1007/978-981-32-9298-7_6

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