The Prediction of Pulverized Coal Ignition Property Based on Piecewise Least Squares Support Vector Machine

被引:0
作者
Chang Aiying [1 ]
Wu Tiejun [1 ]
Xin Bao [1 ]
机构
[1] Zhejiang Univ, State Key Lab Ind Control Technol, Hangzhou, Zhejiang, Peoples R China
来源
PROCEEDINGS OF 2010 3RD IEEE INTERNATIONAL CONFERENCE ON COMPUTER SCIENCE AND INFORMATION TECHNOLOGY (ICCSIT 2010), VOL 6 | 2010年
关键词
subsection model; least squares support vector machine; blending coal; igniting temperature; SPECTROSCOPY;
D O I
暂无
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
Aimed at the quantitative analysis of pulverized coal ignition temperature, this paper presents a piecewise least squares support vector machine modeling method, where several sub-models are created according to the burning characteristics of lignite, bituminous coal, lean coal and anthracite coal etc. and the parameters of each sub-model are optimized independently. By implementing the piecewise LSSVM and the global LSSVM on coal fuel samples obtained from certain company, we find that the piecewise LSSVM behaves better than the global LSSVM on mean- square error and correlation coefficient, etc.
引用
收藏
页码:251 / 254
页数:4
相关论文
共 50 条
  • [31] Blasting vibration velocity prediction based on least squares support vector machine with particle swarm optimization algorithm
    Yuan, Qing
    Zhai, Shihong
    Wu, Li
    Chen, Peishuai
    Zhou, Yuchun
    Zuo, Qingjun
    GEOSYSTEM ENGINEERING, 2019, 22 (05) : 279 - 288
  • [32] Demand Elasticity Analysis by Least Squares Support Vector Machine
    Xie, Li
    Zheng, Hua
    2013 6TH INTERNATIONAL CONGRESS ON IMAGE AND SIGNAL PROCESSING (CISP), VOLS 1-3, 2013, : 1085 - 1089
  • [33] A Novel Least Squares Support Vector Machine Kernel for Approximation
    Mu, Xiangyang
    Gao, Weixin
    Tang, Nan
    Zhou, Yatong
    2008 7TH WORLD CONGRESS ON INTELLIGENT CONTROL AND AUTOMATION, VOLS 1-23, 2008, : 4510 - +
  • [34] Application of Least Squares Support Vector Machine on vehicle recognition
    Yang, Kuihe
    Shan, Ganlin
    Zhao, Lingling
    ISDA 2006: SIXTH INTERNATIONAL CONFERENCE ON INTELLIGENT SYSTEMS DESIGN AND APPLICATIONS, VOL 1, 2006, : 217 - 221
  • [35] Least Squares Support Vector Machine for Constitutive Modeling of Clay
    Zhou, X.
    Shen, J.
    INTERNATIONAL JOURNAL OF ENGINEERING, 2015, 28 (11): : 1571 - 1578
  • [36] Fuzzy Least Squares Support Vector Machine with Fuzzy Hyperplane
    Chien-Feng Kung
    Pei-Yi Hao
    Neural Processing Letters, 2023, 55 : 7415 - 7446
  • [37] Confidence and prediction intervals for semiparametric mixed-effect least squares support vector machine
    Cheng, Qiang
    Tezcan, Jale
    Cheng, Jie
    PATTERN RECOGNITION LETTERS, 2014, 40 : 88 - 95
  • [38] An adaptive least squares support vector machine model with a novel update for NOx emission prediction
    Lv, You
    Yang, Tingting
    Liu, Jizhen
    CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS, 2015, 145 : 103 - 113
  • [39] Combination kernel function least squares support vector machine for chaotic time series prediction
    Tian Zhong-Da
    Gao Xian-Wen
    Shi Tong
    ACTA PHYSICA SINICA, 2014, 63 (16)
  • [40] Discussion about nonlinear time series prediction using least squares support vector machine
    Xu, RR
    Bian, GX
    Gao, CF
    Chen, TL
    COMMUNICATIONS IN THEORETICAL PHYSICS, 2005, 43 (06) : 1056 - 1060