The following publications are possibly variants of this publication:
- Multivariate Time-Series Modeling for Forecasting Sintering Temperature in Rotary Kilns Using DCGNetXiaogang Zhang, Yanying Lei, Hua Chen 0008, Lei Zhang, Yicong Zhou. tii, 17(7):4635-4645, 2021. [doi]
- The Predictive Control of Sintering Temperature in Rotary Kiln Based on Image Feedback and Soft ComputingXiaogang Zhang, Hua Chen, Jing Zhang. icnc 2007: 39-43 [doi]
- Long-term Spatio-Temporal Forecasting via Dynamic Multiple-Graph AttentionWei Shao, Zhiling Jin, Shuo Wang, Yufan Kang, Xiao Xiao, Hamid Menouar, Zhaofeng Zhang, Junshan Zhang, Flora D. Salim. IJCAI 2022: 2225-2232 [doi]
- Recognition of sintering state in rotary kiln using a robust extreme learning machineHua Chen, Jing Zhang, Hongping Hu, Xiaogang Zhang. ijcnn 2014: 2564-2570 [doi]
- T-S fuzzy neural network predictive control for burning zone temperature in rotary kiln with improved hierarchical genetic algorithmZhong-da Tian, Shujiang Li, Yanhong Wang. ijmic, 25(4):323-334, 2016. [doi]