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The Power Consumption Model of Chiller with Elman Neural Networks for On-line Prediction and Control., и . ICSCIB, том 890 из Advances in Intelligent Systems and Computing, стр. 281-289. Springer, (2018)Real-time performance evaluation and improvement of assembly systems with Bernoulli machines and finite production runs., , , , и . Int. J. Prod. Res., 57 (18): 5749-5766 (2019)Second order Takagi-Sugeno fuzzy model with domain adaptation for nonlinear regression., , , и . Inf. Sci., (2021)Hybrid Bidirectional Rapidly Exploring Random Tree Path Planning Algorithm with Reinforcement Learning., , , , и . J. Adv. Comput. Intell. Intell. Informatics, 25 (1): 121-129 (2021)Transient Performance Evaluation of Flexible Production Lines With Two Bernoulli Machines and Dedicated Buffers*., , , и . CASE, стр. 836-841. IEEE, (2020)Analysis and improvement of batch-based production lines with Bernoulli machines., , , и . CASE, стр. 13-18. IEEE, (2014)Remaining Useful Life Prediction of Equipment Based on XGBoost., , и . CSAE, стр. 59:1-59:6. ACM, (2021)Closed Bernoulli lines with finite buffers: real-time performance analysis, completion time bottleneck and carrier control., , и . Int. J. Control, 94 (7): 1994-2007 (2021)DO-UNet: Improved UNet Model for CT Image Segmentation using DBB and Octave Convolution., , , , и . ICCVIT, стр. 22:1-22:8. ACM, (2023)Finite production run-based performance evaluation of assembly systems with Bernoulli machines., , , и . SysCon, стр. 1-7. IEEE, (2018)