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| 1 | A new approach for function approximation in boiler combustion optimization based on modified structural AOSVR 显示文摘 | Si Fengqi Carlose Romerob Yao Zheng | 2009 | Expert System with Applications2009，36，4： | 1 |
| 2 | Optimization of coal-fired boiler SCRs based on modified support vector machine models and genetic algorithms显示文摘 | SI Fengqi ROMERO Carlos E YAO Zheng | 2009 | Fuel2009，88，5： | 1 |
| 3 | A new approach for function approximation in boiler combustion optimization based on modified structural AOSVR显示文摘 | Fengqi Si Romero C E Zheng Yao | 2009 | Expert Systems with Applications2009，36，4： | 1 |
| 4 | Inferential sensor for on-line monitoring of ammonium bisulfate formation temperature in coal-fired power plants显示文摘 | Fengqi Si Carlos E. Romero Zheng Yao Zhigao Xu Robert L. Morey Barry N. Liebowitz | 2008 | Fuel Processing Technology2008，，1： | 1 |
| 5 | Optimization of coal-fired boiler SCRs based on modified support vector machine models and genetic algorithms显示文摘 | Si Fengqi Romero C E Yao Zheng | 2009 | Fuel2009，88，5： | 1 |
| 6 | A new approach for function approximation in boiler combustion optimization based on modified structural AOSVR 显示文摘 | SI Fengqi ROMERO C E YAO Zheng | 2009 | Expert Systems with Applications2009，36，4： | 1 |
| 7 | An integrated theoretical fouling model for convective heating surfaces in coal-fired boilers显示文摘 | Pan Yadi Si Fengqi Xu Zhigao | | 0，，02： | 1 |
| 8 | A new approach for function approximation in boiler combustion optimization based on modified structural AOSVR显示文摘 | Si Fengqi Romero C E Yao Zheng | | 0，，04： | 1 |
| 9 | Evolved clustering analysis of 300 MW boiler furnace pressure sequence based on entropy characterization显示文摘The furnace process is very important in boiler operation,and furnace pressure works as an important parameter in furnace process.Therefore,there is a need to analyze and monitor the pressure signal in furnace.However,little work has been conducted on the relationship with the pressure sequence and boiler’s load under different working conditions.Since pressure sequence contains complex information,it demands feature extraction methods from multi-aspect consideration.In this paper,fuzzy c-means analysis method based on weighted validity index(VFCM)has been proposed for the working condition classification based on feature extraction.To deal with the fluctuating and time-varying pressure sequence,feature extraction is taken as nonlinear analysis based on entropy theory.Three kinds of entropy values,extracted from pressure sequence in time-frequency domain,are studied as the clustering objects for work condition classification.Weighted validity index,taking the close and separation degree into consideration,is calculated on the base of Silhouette index and Krzanowski-Lai index to obtain the optimal clustering number.Each time FCM runs,the weighted validity index evaluates the clustering result and the optimal clustering number will be obtained when it reaches the maximum value.Four datasets from UCI Machine Learning Repository are presented to certify the effectiveness in VFCM.Pressure sequences got from a 300 MW boiler are then taken for case study.The result of the pressure sequence case study with an error rate of 0.5332%shows the valuable information on boiler’s load and pressure sequence in furnace.The relationship between boiler’s load and entropy values extracted from pressure sequence is proposed.Moreover,the method can be considered to be a reference method for data mining in other fluctuating and time-varying sequences. | GU Hui REN ShaoJun SI FengQi XU ZhiGao ZHAO LingLing | 2016 | Science China(Technological Sciences)2016，59，4： | 0 |
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