American Journal of Applied Mathematics

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Application of Neural Network Model in an Epidemiological Study

Received: 19 July 2015    Accepted: 24 July 2015    Published: 01 August 2015
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Abstract

This paper use the neural network model to an epidemiological study, i.e. bovine tuberculosis (bTB) occurrence in cattle herds, together with well-established risk factors in the area known as West Wicklow, in the east of Ireland. The binary target variable is whether the herd is in the restricted status, which is defined by whether any bTB reactor is detected in the herd. To estimate the parameters and prevent over-fitting in neural network model fitting, the observations are divided into three part of Training data set, Validation data set, and Test data set. By analysis on the lift charts on test data set, the fitted neural network model can be used to enhance practice efficiency.

DOI 10.11648/j.ajam.20150304.16
Published in American Journal of Applied Mathematics (Volume 3, Issue 4, August 2015)
Page(s) 201-205
Creative Commons

This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.

Copyright

Copyright © The Author(s), 2024. Published by Science Publishing Group

Keywords

Neural Network Model, Bovine Tuberculosis, Spearman’s Rank Correlation, Lift Chart

References
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[8] Gordejo, R.F.J., Vermeersch, J.P., 2006. Towards eradication of bovine tuberculosis in the European Union. European Union Veterinary Microbiology 112, 101-109.
[9] Griffin, J.M., Hahesya, T., Lyncha, T., M.D. Salmanb, M.D., McCarthya, J., Hurleya, T., 1993. The association of cattle husbandry practices, environmental factors and farmer characteristics with the occurence of chronic bovine tuberculosis in dairy herds in the Republic of Ireland. Preventive Veterinary Medicine 17, 145-160.
[10] Griffin, J.M., Williams, D.H., Kelly, G.E., Clegg, T.A., O’Boyle, I., Collins, J.D., More, S.J., 2005. The impact of badger removal on the control of tuberculosis in cattle herds in Ireland. Preventive Veterinary Medicine 67, 237–266.
[11] Hahesy, T., Kelleher, D.L., Doherty, J., 1992. An investigation of a possible association between the occurrence of bovine tuberculosis and weather variables. Irish Veterinary Journal 45, 127-128.
[12] Kattamuri S. Sarma (2013). Predictive Modeling with SAS Enterprise Miner Practical Solutions for Business Applications Second Edition. NC: SAS Institute Inc, Cary.
[13] Kologlu M., Elker D., Altun H., Sayek I. (2001) Valdation of MPI and OIA II in two different groups of patients with secondary peritonitis // Hepato-Gastroenterology. – 2001. – Vol. 48, No. 37. – P. 147-151.
[14] Manro, S. and Kumam, P.(2012) Common fixed point theorems for expansion mappings in various abstract spaces using the concept of weak reciprocal continuity, Fixed Point Theory and Applications, 2012:221.
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Author Information
  • School of Information, Beijing Wuzi University, Beijing, China

  • School of Information, Beijing Wuzi University, Beijing, China

  • School of Information, Beijing Wuzi University, Beijing, China

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    Renhao Jin, Fang Yan, Jie Zhu. (2015). Application of Neural Network Model in an Epidemiological Study. American Journal of Applied Mathematics, 3(4), 201-205. https://doi.org/10.11648/j.ajam.20150304.16

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    ACS Style

    Renhao Jin; Fang Yan; Jie Zhu. Application of Neural Network Model in an Epidemiological Study. Am. J. Appl. Math. 2015, 3(4), 201-205. doi: 10.11648/j.ajam.20150304.16

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    AMA Style

    Renhao Jin, Fang Yan, Jie Zhu. Application of Neural Network Model in an Epidemiological Study. Am J Appl Math. 2015;3(4):201-205. doi: 10.11648/j.ajam.20150304.16

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  • @article{10.11648/j.ajam.20150304.16,
      author = {Renhao Jin and Fang Yan and Jie Zhu},
      title = {Application of Neural Network Model in an Epidemiological Study},
      journal = {American Journal of Applied Mathematics},
      volume = {3},
      number = {4},
      pages = {201-205},
      doi = {10.11648/j.ajam.20150304.16},
      url = {https://doi.org/10.11648/j.ajam.20150304.16},
      eprint = {https://download.sciencepg.com/pdf/10.11648.j.ajam.20150304.16},
      abstract = {This paper use the neural network model to an epidemiological study, i.e. bovine tuberculosis (bTB) occurrence in cattle herds, together with well-established risk factors in the area known as West Wicklow, in the east of Ireland. The binary target variable is whether the herd is in the restricted status, which is defined by whether any bTB reactor is detected in the herd. To estimate the parameters and prevent over-fitting in neural network model fitting, the observations are divided into three part of Training data set, Validation data set, and Test data set. By analysis on the lift charts on test data set, the fitted neural network model can be used to enhance practice efficiency.},
     year = {2015}
    }
    

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    AU  - Renhao Jin
    AU  - Fang Yan
    AU  - Jie Zhu
    Y1  - 2015/08/01
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    AB  - This paper use the neural network model to an epidemiological study, i.e. bovine tuberculosis (bTB) occurrence in cattle herds, together with well-established risk factors in the area known as West Wicklow, in the east of Ireland. The binary target variable is whether the herd is in the restricted status, which is defined by whether any bTB reactor is detected in the herd. To estimate the parameters and prevent over-fitting in neural network model fitting, the observations are divided into three part of Training data set, Validation data set, and Test data set. By analysis on the lift charts on test data set, the fitted neural network model can be used to enhance practice efficiency.
    VL  - 3
    IS  - 4
    ER  - 

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