|
1、X.L. Chen, P.H. Wang, Q. Wang, Y.H. Dong, A Two-Stage strategy to handle equality constraints in ABC-based power economic dispatch problems [J], Soft Computing, 2019. (SCI) 2、X.L. Chen, P.H. Wang, Y.S. Hao, et al, Evidential KNN-Based Condition Monitoring and Early Warning Method with Applications in Power Plant [J], Neurocomputing, 2018, 315: 18-32. (SCI) 3、Y. Zhao, P.H. Wang, Y. G. Li, et al. Fuzzy weighted c -harmonic regressions clustering algorithm[J]. Soft Computing, 2017(4):1-17. (SCI) 4、Y.S. Hao, Z.G. Su, P.H. Wang, et al., Constrained fuzzy evidential multivariate model identified by EM algorithm: a soft sensor to monitoring imprecise and uncertain process parameters [J], Soft Computing, 2017, 21(6): 1619-1642. (SCI) 5、Q. Wang, P.H. Wang, Z.G. Su. An Analytical model on thermal performance evaluation of counter flow wet cooling tower [J]. Thermal Science, 2017, 21(6).(SCI) 6、Z.G. Su, P.H. Wang, Likelihood-based multivariate fuzzy model with linear inequality constraints [J], Journal of Intelligent and Fuzzy Systems, 2015, 27(5): 2191~2209. (SCI) 7、Q. Wang, Z.G. Su, B. Rezaee, P.H. Wang, Constructing T–S fuzzy model from imprecise and uncertain knowledge represented as fuzzy belief functions[J], Neurocomputing, 2015, 166: 319-336. (SCI) 8、Z.G. Su, P.H. Wang, Likelihood-based multivariate fuzzy model with linear inequality constraints [J], Journal of Intelligent and Fuzzy Systems, 2015, 27(5): 2191~2209. (SCI) 9、Z.G. Su, P.H. Wang, Y.G. Li, et al. Parameter estimation from interval-valued data using the expectation-maximization algorithm[J], Journal of Statistical Computation and Simulation, 2015, 85(2):320-338. (SCI) 10、Z.G. Su, P.H. Wang. Regression analysis of belief functions on interval-valued variables: comparative studies [J], Soft Computing, 2014, 18(1):51-70. (SCI) 11、Z.G. Su, Y.F. Wang, P.H. Wang, Parametric regression analysis of imprecise and uncertain data in the fuzzy belief function framework [J], International Journal of Approximate Reasoning, 2013, 54(8): 1217-1242. (SCI) 12、Z.G. Su, P.H. Wang, Z.L. Song, Kernel based nonlinear fuzzy regression model [J], Engineering Applications of Artificial Intelligence, 2013, 26(2): 724-738. (SCI) 13、Z.G. Su, P.H. Wang, J. Shen, et al, Convenient T–S fuzzy model with enhanced performance using a novel swarm intelligent fuzzy clustering technique[J], Journal of Process Control, 2012, 22(1): 108-124. (SCI) 14、Z.G. Su, P.H. Wang, J. Shen, et al, Automatic fuzzy partitioning approach using Variable string length Artificial Bee Colony (VABC) algorithm[J]. Applied soft computing, 2012, 12(11): 3421-3441. (SCI) 15、Z.G. Su, P.H. Wang, Minimizing neighborhood evidential decision error for feature evaluation and selection based on evidence theory [J], Expert Systems with Applications, 2012, 39(1): 527-540. (SCI) 16、Z.G. Su, P.H. Wang, X.J. Yu, et al, Maximal confidence intervals of the interval-valued belief structure and applications[J], Information Sciences, 2011, 181(9): 1700-1721. (SCI) 17、Z.G. Su, P.H. Wang, J. Shen, et al, Multi-model strategy based evidential soft sensor model for predicting evaluation of variables with uncertainty[J], Applied Soft Computing, 2011, 11(2):2595-2610. (SCI) 18、Z.G. Su, P.H. Wang, X.J. Yu, Immune genetic algorithm-based adaptive evidential model for estimating unmeasured parameter: Estimating levels of coal powder filling in ball mill [J], Expert Systems with Applications, 2010, 37(7): 5246-58. (SCI) 19、Z.G. Su, P.H. Wang, Improved adaptive evidential k-NN rule and its application for monitoring level of coal powder filling in ball mill [J], Journal of Process Control, 2009, 19(10): 1751-1762. (SCI) 20、Z.G. Su, P.H. Wang, X.J. Yu, et al, Experimental investigation of vibration signal of an industrial tubular ball mill: Monitoring and diagnosing [J], Minerals Engineering, 2008, 21(10): 699-710. (SCI) 21、H. Pan, P.H. Wang, Online Measurement System of Pulverized-Coal Concentration in Power Plant[C], 2018 4th International Conference on Renewable Energy Technologies, ICRET 2018, Chengdu, 2018.1.16 - 2018.1.18. (EI) 22、M. Zhao, Y. Zhao, P.H. Wang, J.Q. Du, Wrapper full-scale sample selection algorithm for thermal process modeling[C], 2nd International Conference on Materials Science, Energy Technology and Power Engineering, MEP 2018, Hangzhou, 2018.4.14-2018.4.15. (EI) 23、C.C. Cai, P.H. Wang, F.R. Shen, A novel direct distribution method based on dynamic characteristic coefficient for combined heat and power dispatch in single extraction units[C], 2017 2nd International Conference on Power and Renewable Energy (ICPRE). IEEE, 2017: 698-703. (EI) 24、X.L. Chen, P.H. Wang, M. Zhao, J.Y. Liang, Fault early warning method via density peaks clustering for the equipment in power plants [C], 60th ISA POWID Symposium, Cleveland, OH, USA, June 2017. (EI) 25、T. Zhang, P.H. Wang, Y.K. Liu, Y.L. Qiu, A real-time synchronization algorithm to estimate indirect balance, 60th ISA POWID Symposium, Cleveland, OH, USA, June 2017. (EI) 26、G. Zhao, P.H. Wang, Z.G. Su, et al, Disturbance observer-based model predictive control for bed temperature of CFB boiler: Improvements and comparisons[C], 59th ISA POWID Symposium, USA, June 2016. (EI) 27、X.L. Chen, P.H. Wang, Research on the assessment method of residential district line loss rate based on statistical regulation of marketing data[C], Energy and Mechanical Engineering: Proceedings of 2015 International Conference on Energy and Mechanical Engineering. (ISTP) 28、X.S. Quan, P.H. Wang, Y.S. Hao, et al, Analysis of Line Loss Based on Matlab and Oracle Database[C], Third International Conference on Advanced Cloud & Big Data, IEEE Computer Society, 2015. (EI) 29、J.S. Ge, P.H. Wang, J. Yin, Study on Algorithm for Soft Computing Coal-Fired Calorific Value of Utility Boiler[C], Second International Conference on Intelligent System Design & Engineering Application, IEEE, 2012. (EI) 30、X.Y. Zhao, P.H. Wang, B. Li, Soft Sensor Modeling for the Efficiency of Steam Turbine Last Stage Group Using Support Vector Machine Regression[C], Second International Conference on Intelligent System Design & Engineering Application. IEEE, 2012. (EI) 31、Y.S. Zhang, P.H. Wang, J. Yin, Optimizing the Excess Air Ratio of Coal-Fired Boiler[C], 2012 International Conference on Intelligent System Design and Engineering Application, IEEE Computer Society, 2012. (EI) 32、J. Qian, P.H. Wang, H. Zhao, et al, Research of Real-time Monitoring Model for Calculating Exhaust Enthalpy[C], Power & Energy Engineering Conference, IEEE, 2010. 33、Q. Wang, P.H. Wang, Matrix Method Research on the System Utilization of the Shaft Seal Steam Based on the Equivalent Enthalpy Drop Theory [C], Asia-pacific Power & Energy Engineering Conference, IEEE, 2009. (EI) 34、江承潮, 王培红, 郝勇生, 赵明, 李孟阳, 梁俊宇, 光煤互补发电系统集成方案研究与性能分析[J], 太阳能学报, 2018, 39(4): 988-995. (EI) 35、赵阳, 王培红, 苏志刚, 李益国, 朱晓瑾, 基于鲁棒模糊C-均值回归的TS建模方法及其在热工过程中的应用[J], 中国电机工程学报, 2018, 38(7): 2063-2069+2221. (EI) 36、权学森, 王培红, 赵刚, 赵明, 李孟阳, 梁俊宇, 基于槽式太阳能辅助燃煤发电系统的蓄热系统设计[J], 太阳能学报, 2017, 38(12): 3216-3221. (EI) 37、赵春, 王培红, 燃气-蒸汽联合循环热经济学分析评价指标研究[J], 中国电机工程学报, 2013, 33(23): 44-50. (EI) 38、王乾, 王培红, 苏志刚, 汽轮机及其热力系统性能分析与优化[J]. 东南大学学报:自然科学版, 2012(S2): 276-280. (EI) 39、赵欢, 王培红, 陆璐, 电站锅炉热效率与NO_x排放响应特性建模方法[J], 中国电机工程学报, 2008(32): 96-100. (EI) 40、苏志刚, 王培红, 于向军, 中储式制粉系统出力在线监测软测量建模[J], 中国电机工程学报, 2007, 27(29): 90-95. (EI) 41、钱瑾, 王培红, 李琳, 聚类算法在锅炉运行参数基准值分析中的应用[J], 中国电机工程学报, 2007(23): 71-74. (EI) 42、王培红, 李磊磊, 陈强, 董益华, 人工智能技术在电站锅炉燃烧优化中的应用研究[J], 中国电机工程学报, 2004(04): 188-192. (EI) 43、程懋华, 王培红, 高亹, 汽轮发电机组回热系统通用热平衡方程及其结构模型研究[J], 中国电机工程学报, 2002(04): 67-72. (EI) 44、王培红, 贾俊颖, 金旭英, 再热机组热力循环效果的评价及其算法研究[J], 中国电机工程学报, 2002(03): 69-72. (EI) 45、王培红, 吕沥峰, 李磊磊, 汽轮机热力系统的节能改造与回热效果评价[J]. 汽轮机技术, 2000, 42(6): 344-348. (EI) 46、王培红, 马文智, 汽轮机热经济性分析中给水泵效率的影响及其算法研究[J]. 动力工程学报, 1997(3): 43-47. (EI)
|
