88 citations to 10.1016/j.neunet.2017.12.007 (Crossref Cited-By Service)
  1. Jing Liang, Hao Guo, Ke Chen, Kunjie Yu, Caitong Yue, Xia Li, “An improved Kalman particle swarm optimization for modeling and optimizing of boiler combustion characteristics”, Robotica, 41, № 4, 2023, 1087  crossref
  2. Domenico Altieri, Martin K. Patel, Joël Lazarus, Giovanni Branca, “Numerical analysis of low-cost optimization measures for improving energy efficiency in residential buildings”, Energy, 273, 2023, 127257  crossref
  3. Francesco Calabrò, Gianluca Fabiani, Constantinos Siettos, “Extreme learning machine collocation for the numerical solution of elliptic PDEs with sharp gradients”, Computer Methods in Applied Mechanics and Engineering, 387, 2021, 114188  crossref
  4. Alex D. Assis, Luiz C. B. Torres, Lourenco R. G. Araujo, Vitor M. Hanriot, Antonio P. Braga, “Neural Networks Regularization With Graph-Based Local Resampling”, IEEE Access, 9, 2021, 50727  crossref
  5. Jae Jung Han, Hyun-jung Kim, “Stock price prediction using multiple valuation methods based on artificial neural networks for KOSDAQ IPO companies”, Investment Analysts Journal, 50, № 1, 2021, 17  crossref
  6. Tim De Ryck, Samuel Lanthaler, Siddhartha Mishra, “On the approximation of functions by tanh neural networks”, Neural Networks, 143, 2021, 732  crossref
  7. Yu Mei, Jiaqian Yang, Yin Lu, Feilin Hao, Dongmei Xu, Hua Pan, Jiade Wang, “BP–ANN Model Coupled with Particle Swarm Optimization for the Efficient Prediction of 2-Chlorophenol Removal in an Electro-Oxidation System”, IJERPH, 16, № 14, 2019, 2454  crossref
  8. Yunyou Qian, Dansheng Yu, “Rates of approximation by neural network interpolation operators”, Applied Mathematics and Computation, 418, 2022, 126781  crossref
  9. Huilin Ge, Feng Jiang, Zhenkai Zhang, 2019 IEEE 8th Joint International Information Technology and Artificial Intelligence Conference (ITAIC), 2019, 1280  crossref
  10. Zhongyang Zhu, Guangmin Sun, Cunfu He, “An intelligent approach for simultaneously performing material type recognition and case depth prediction in two types of surface-hardened steel rods using a magnetic hysteresis loop”, Meas. Sci. Technol., 30, № 10, 2019, 105601  crossref
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