The following publications are possibly variants of this publication:
- Eigen-flame image-based robust recognition of burning states for sintering process control of rotary kilnWeitao Li, Kezhi Mao, Xiaojie Zhou, Tianyou Chai, Hong Zhang. cdc 2009: 398-403 [doi]
- Flame Image-Based Burning State Recognition for Sintering Process of Rotary Kiln Using Heterogeneous Features and Fuzzy IntegralWeitao Li, Dianhui Wang, Tianyou Chai. tii, 8(4):780-790, 2012. [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]
- Burning state recognition of rotary kiln using ELMs with heterogeneous featuresWeitao Li, Dianhui Wang, Tianyou Chai. ijon, 102:144-153, 2013. [doi]
- Simulated Feedback Mechanism-Based Rotary Kiln Burning State Cognition Intelligence MethodKeqiong Chen, Jianping Wang, Weitao Li, Wei Li, Yi Zhao. access, 5:4458-4469, 2017. [doi]
- GLCM Based Extraction of Flame Image Texture Features and KPCA-GLVQ Recognition Method for Rotary Kiln Combustion Working ConditionsJie-Sheng Wang, Xiu-Dong Ren. ijautcomp, 11(1):72-77, 2014. [doi]
- Recognition of the Temperature Condition of a Rotary Kiln Using Dynamic Features of a Series of Blurry Flame ImagesHua Chen, Xiaogang Zhang, Pengyu Hong, Hongping Hu, Xiang Yin. tii, 12(1):148-157, 2016. [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]
- Multisource Data Ensemble Modeling for Clinker Free Lime Content Estimate in Rotary Kiln Sintering ProcessesWeitao Li, Dianhui Wang, Tianyou Chai. tsmc, 45(2):303-314, 2015. [doi]