期刊文献+

Subspace identification for a stochastic model of plague 被引量:4

Subspace identification for a stochastic model of plague
原文传递
导出
摘要 In this paper, a stochastic model of plague is first studied by subspace identification. First, the discrete model of plague is obtained based on the classical model. The corresponding stochastic model is proposed for the existence of stochastic disturbances. Second, for the model, the parameter matrices and noise intensity are obtained. Finally, the simulations of the model show that the subspace identification is more precise than least square method.
出处 《International Journal of Biomathematics》 2016年第5期85-105,共21页 生物数学学报(英文版)
基金 Acknowledgments This work was supported by the National Natural Science Foundation of China (NSFC) under Grant 61374137 and the State Key Laboratory of Integrated Automation of Process Industry Technology and Research Center of National Metallurgical Automation Fundamental Research Funds (2013ZCX02-03).
关键词 Subspace method system identification stochastic biological model PLAGUE 子空间辨识 随机模型 鼠疫 最小二乘法 离散模型 经典模型 随机扰动 噪声强度
  • 相关文献

参考文献21

  • 1C. M. Bauer, G. Nachman, S. M. Lewis, L. Faust and J. Michael Reed, Modeling effects of harvest on firefly population persistence, Ecol. Model. 256 (2013) 43-52.
  • 2V. Boonyapinyo and T. Janesupasaeree, Data-driven stochastic subspace identifica- tion of flutter derivatives of bridge decks, J. Wind Engrg. Indust. Aerodynam. 98 (2010) 784-799.
  • 3G. Christakos, R. A. Olea and H.-L. Yu, Recent results on the spatiotemporal mod- elling and comparative analysis of Black Death and bubonic plague epidemics, Public Health 121 (2007) 700-720.
  • 4W. Favoreel, B. De Moor and P. Van Overschee, Subspace state space system iden- tification for industrial processes, J. Process Control 10 (2000) 149-155.
  • 5J. Heydari, C. Lawless, D. A. Lydall and D. J. Wilkinson, Fast Bayesian parameter estimation for stochastic logistic growth models, Biosystems 122 (2014) 55-72.
  • 6I. W. Jamaludin, N. A. Wahab, N. S. Khalid, S. Sahlan, Z. Ibrahim and M. F. Rahmat, N4SID and MOESP subspace identification methods, in IEEE 9th Int. Col- loquium on Signal Processing and Its Applications (2013), pp. 140-145.
  • 7K. Kameyama and A. Ohsumi, Subspace-based prediction of linear time-varying stochastic systems, Automatica 43 (2007) 2009-2021.
  • 8W. M. Lotfy, Plague in Egypt: Disease biology, history and contemporary analysis: A minireview, J. Adv. Res. 6 (2015) 549-554.
  • 9S. Monecke, H. Monecke and J. Monecke, Modelling the Black Death. A historical case study and implications for the epidemiology of bubonic plague, Int. J. Med. Microbiol. 299 (2009) 582-593.
  • 10A. Ohsumi, K. Kameyama and K.-I. Yamaguchi, Subspace identification for continuous-time stochastic systems via distribution-based approach, Automatica 38 (2002) 63-79.

同被引文献6

引证文献4

二级引证文献9

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部