1,136
Views
4
CrossRef citations to date
0
Altmetric
Articles

Hierarchical-fuzzy allocation and multi-parameter adjustment prediction for industrial loading optimisation

, ORCID Icon, , , &
Pages 687-708 | Received 12 Oct 2021, Accepted 13 Jan 2022, Published online: 31 Jan 2022

References

  • Che, P., Liu, Y., Che, L., & Lang, J. (2020). Co-Optimization of generation Self-Scheduling and coal supply for Coal-Fired power plants. IEEE Access, 8, 110633–110642. https://doi.org/10.1109/access.2020.2989514
  • Çınar, A., & Tuncer, S. A. (2021). Classification of normal sinus rhythm, abnormal arrhythmia and congestive heart failure ECG signals using LSTM and hybrid CNN-SVM deep neural networks. Computer Methods in Biomechanics and Biomedical Engineering, 24(2), 203–214. https://doi.org/10.1080/10255842.2020.1821192
  • Du, J., Vong, C., & Chen, C. L. P. (2021). Novel efficient RNN and LSTM-like architectures: Recurrent and gated broad learning systems and their applications for text classification. IEEE Transactions on Cybernetics, 51(3), 1586–1597. https://doi.org/10.1109/TCYB.2020.2969705
  • Duguma, D. G., Kim, J., Lee, S., Jho, N., Sharma, V., & You, I. (2021). A lightweight D2D security protocol with request-forecasting for next-generation mobile networks. Connection Science, 1–25. https://doi.org/10.1080/09540091.2021.2002812
  • Han, Y., Li, C., Zhang, W., & Ahmad, H. G. (2020). Impulsive consensus of multiagent systems with limited bandwidth based on encoding–decoding. IEEE Transactions on Cybernetics, 50(1), 36–47. https://doi.org/10.1109/TCYB.2018.2863108
  • He, Z., Zhou, Z., Gan, L., Huang, J., & Zeng, Y. (2019). Chinese entity attributes extraction based on bidirectional LSTM networks. International Journal of Computational Science and Engineering, 18(1), 65. https://doi.org/10.1504/IJCSE.2019.096988
  • Jani, M., Garg, P., & Gupta, A. (2020). Performance analysis of a mixed cooperative PLC–VLC system for indoor communication systems. IEEE Systems Journal, 14(1), 469–476. https://doi.org/10.1109/JSYST.2019.2911717
  • Ji, Y., Xu, K., Zeng, P., & Zhang, W. (2021). GA-SVR algorithm for improving forest above ground biomass estimation using SAR data. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 14, 6585–6595. https://doi.org/10.1109/JSTARS.2021.3089151
  • Kara, A. (2021). Multi-step influenza outbreak forecasting using deep LSTM network and genetic algorithm. Expert Systems with Applications, 180, 115153. https://doi.org/10.1016/j.eswa.2021.115153
  • Krupa, P., Limon, D., & Alamo, T. (2021). Implementation of model predictive control in programmable logic controllers. IEEE Transactions on Control Systems Technology, 29(3), 1117–1130. https://doi.org/10.1109/TCST.2020.2992959
  • Liang, H., Liu, G., Zhang, H., & Huang, T. (2021). Neural-network-based event-triggered adaptive control of nonaffine nonlinear multiagent systems with dynamic uncertainties. IEEE Transactions on Neural Networks and Learning Systems, 32(5), 2239–2250. https://doi.org/10.1109/TNNLS.2020.3003950
  • Mackenzie, J., Roddick, J. F., & Zito, R. (2019). An evaluation of HTM and LSTM for short-term arterial traffic flow prediction. IEEE Transactions on Intelligent Transportation Systems, 20(5), 1847–1857. https://doi.org/10.1109/TITS.2018.2843349
  • Mou, L., Zhao, P., Xie, H., & Chen, Y. (2019). T-LSTM: A long short-term memory neural network enhanced by temporal information for traffic flow prediction. IEEE Access, 7, 98053–98060. https://doi.org/10.1109/ACCESS.2019.2929692
  • Qiao, F., Ma, Y., Zhou, M., & Wu, Q. (2020). A novel rescheduling method for dynamic semiconductor manufacturing systems. IEEE Transactions on Systems, Man, and Cybernetics: Systems, 50(5), 1679–1689. https://doi.org/10.1109/TSMC.2017.2782009
  • Shu, X., Zhang, L., Sun, Y., & Tang, J. (2021). Host–parasite: Graph LSTM-in-LSTM for group activity recognition. IEEE Transactions on Neural Networks and Learning Systems, 32(2), 663–674. https://doi.org/10.1109/TNNLS.2020.2978942
  • Srivastava, T., Vedanshu, & Tripathi, M. M. (2020). Predictive analysis of RNN, GBM and LSTM network for short-term wind power forecasting. Journal of Statistics and Management Systems, 23(1), 33–47. https://doi.org/10.1080/09720510.2020.1723224
  • Sun, L., & Huo, W. (2016). Adaptive fuzzy control of spacecraft proximity operations using hierarchical fuzzy systems. IEEE/ASME Transactions on Mechatronics, 21(3), 1629–1640. https://doi.org/10.1109/TMECH.2015.2494607
  • Wang, L., Zhou, H., Yang, J., Xiong, Y., She, J., & Chen, W. (2021). A decision support system for tobacco cultivation measures based on BPNN and GA. Computers and Electronics in Agriculture, 181, 105928. https://doi.org/10.1016/j.compag.2020.105928
  • Wu, S., Liu, Y., Zou, Z., & Weng, T. (2021). S_I_LSTM: Stock price prediction based on multiple data sources and sentiment analysis. Connection Science, 1–19. https://doi.org/10.1080/09540091.2021.1940101
  • Xue, H., Huynh, D. Q., & Reynolds, M. (2021). PoPPL: Pedestrian trajectory prediction by LSTM with automatic route class clustering. IEEE Transactions on Neural Networks and Learning Systems, 32(1), 77–90. https://doi.org/10.1109/TNNLS.2020.2975837
  • Yu, R., Chen, Y., Han, B., & Zhao, H. (2021). A hierarchical control design framework for fuzzy mechanical systems with high-order uncertainty bound. IEEE Transactions on Fuzzy Systems, 29(4), 820–832. https://doi.org/10.1109/TFUZZ.2020.2965913
  • Zhang, S., Yu, H., & Zhu, G. (2021). An emotional classification method of Chinese short comment text based on electra. Connection Science, 1–20. https://doi.org/10.1080/09540091.2021.1985968
  • Zhang, S., Zhang, Z., Chen, Z., Lin, S., & Xie, Z. (2021). A novel method of mental fatigue detection based on CNN and LSTM. International Journal of Computational Science and Engineering, 24(3), 290. https://doi.org/10.1504/IJCSE.2021.115656
  • Zhao, Z., Liu, S., Zhou, M., Guo, X., & Qi, L. (2020). Decomposition method for new single-machine scheduling problems from steel production systems. IEEE Transactions on Automation Science and Engineering, 17(3), 1–12. https://doi.org/10.1109/TASE.2019.2953669
  • Zhou, Z., & Xu, H. (2021). Large-scale multiagent system tracking control using mean field games. IEEE Transactions on Neural Networks and Learning Systems, 32(5), 1–9. https://doi.org/10.1109/TNNLS.2021.3071109