DeepSCN Publications

Deep Stochastic Configuration Networks

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DeepSCN

  Publications

  1. Wang, D. and Felicetti, M.J., Stochastic Configuration Machines for Industrial Artificial Intelligence. arXiv preprint arXiv:2308.13570v1, 2023. [PDF]

  2. Wang, D. and Li, M., Stochastic configuration networks: Fundamentals and algorithms. IEEE Trans. On Cybernetics, 47(10), pp. 3466-3479, 2017; arXiv preprint arXiv:1702.03180, 2017. [PDF]

  3. Wang, D. and Li, M., Robust stochastic configuration networks with kernel density estimation for uncertain data regression. Information Sciences, 412-413 (2017) 210-222. [PDF]

  4. Wang, D. and Cui, C., Stochastic configuration networks ensemble with heterogeneous features for large-scale data analytics. Information Sciences, 417 (2017) 55-71. [PDF]

  5. Wang, D. and Li, M., Deep stochastic configuration networks with universal approximation property. arXiv preprint arXiv:1702.05639v4, 2017. (It has been presented and published in the Proceedings of 2018 International Joint Conference on Neural Networks, July 8-13, 2018, Rio de Janeiro, Brazil) . [PDF]

  6. Li, M. and Wang D., 2D stochastic configuration networks for image data analytics. IEEE Trans. On Cybernetics, Accepted June 25, 2019. [PDF]

  7. Huang, C. Huang, Q. and Wang, D., Stochastic configuration networks based adaptive storage replica management for power big data processing. IEEE Trans. on Industrial Informatics, 16(1), pp. 373-383, 2020. [PDF]

  8. Lu, J. and Ding J., Construction of prediction intervals for carbon residual of crude oil based on deep stochastic configuration networks. Information Sciences, 486 (2019) pp. 119–132, 2020. [PDF]

  9. Wang, W. and Wang, D., Prediction of component concentrations in sodium aluminate liquor using stochastic configuration networks. Neural Computing and Applications, https://doi.org/10.1007/s00521-020-04771-4 2020. [PDF]

  10. Lu, J. and Ding J., Mixed-distribution based robust stochastic. configuration networks for prediction interval construction. IEEE Trans. on Industrial Informatics, 2020. [PDF]

  11. Lu, J., Ding J., Dai, X., and Chai T., Ensemble stochastic configuration networks for estimating prediction intervals: A simultaneous robust training algorithm and its application. IEEE Transactions on Neural Networks and Learning Systems, 2020. [PDF]