- Weiying Zeng, Mohammed A. S. Khalid, Xiaoye Han, Jimi Tjong, “A Study on Extreme Learning Machine for Gasoline Engine Torque Prediction”, IEEE Access, 8, 2020, 104762
- Shao-Bo Lin, “Limitations of shallow nets approximation”, Neural Networks, 94, 2017, 96
- Pournamasi Parhi, Ranjeeta Bisoi, Pradipta Kishore Dash, “An improvised nature-inspired algorithm enfolded broad learning system for disease classification”, Egyptian Informatics Journal, 24, № 2, 2023, 241
- Te-Jen Chang, Shan-Jen Cheng, Chang-Hung Hsu, Jr-Ming Miao, Shih-Feng Chen, “Prognostics for remaining useful life estimation in proton exchange membrane fuel cell by dynamic recurrent neural networks”, Energy Reports, 8, 2022, 9441
- Namig J. Guliyev, Vugar E. Ismailov, “On the approximation by single hidden layer feedforward neural networks with fixed weights”, Neural Networks, 98, 2018, 296
- Wei Gao, Luhe Wan, Shaoqun Qi, Di Wang, “The Tracing of Wastewater in Enterprises Based on Hybrid Neural Network”, Journal of Coastal Research, 97, № sp1, 2019, 1
- Deep Ray, Jan S. Hesthaven, “An artificial neural network as a troubled-cell indicator”, Journal of Computational Physics, 367, 2018, 166
- 佳玄 于, “A Recommendation Model Integrating User Trust Relationship and Neural Network”, MOS, 12, № 03, 2023, 1807
- Haoran Shen, Yifei Jiang, Yuanting Yan, 2021 16th International Conference on Intelligent Systems and Knowledge Engineering (ISKE), 2021, 579
- Namig J. Guliyev, Vugar E. Ismailov, “Approximation capability of two hidden layer feedforward neural networks with fixed weights”, Neurocomputing, 316, 2018, 262