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Research Article | Open Access |

Experimental Study on an Efficient Dengue Disease Management System

Author 1: J M.M.C Jayasuriya Author 2: G.K.K.T.Galappaththi Author 3: M.A.Dilupa Sampath Author 4: H.N.Nipunika Author 5: W.H. Rankothge
International Journal of Advanced Computer Science and Applications (IJACSA) · Vol. 9, No. 11 · Published 2018 · Cited by 11

DOI: https://doi.org/10.14569/IJACSA.2018.091107

Abstract

Dengue has become a serious health hazard in Sri Lanka with the increasing cases and loss of human lives. It is necessary to develop an efficient dengue disease management system which could predict the dengue out breaks, plan the countermeasures accordingly and allocate resources for the countermeasures. We have proposed a platform for Dengue disease management with following modules: (1) a prediction module to predict the dengue outbreak and (2) an optimization algorithm module to optimize hospital staff according to the predictions made on future dengue patient counts. This paper focuses on the optimization algorithm module. It has been developed based on two approaches: (1) Genetic Algorithm (GA) and (2) Iterated Local Search (ILS). We are presenting the performances of our optimization algorithm module with a comparison of the two approaches. Our results show that the GA approach is much more efficient and faster than the ILS approach.

Keywords

How to Cite this Article

Jayasuriya, J. M., G.K.K.T.Galappaththi, Sampath, M., H.N.Nipunika, & Rankothge, W. (2018). Experimental Study on an Efficient Dengue Disease Management System. International Journal of Advanced Computer Science and Applications, 9(11). https://doi.org/10.14569/IJACSA.2018.091107

Jayasuriya, J M.M.C, et al.. "Experimental Study on an Efficient Dengue Disease Management System." International Journal of Advanced Computer Science and Applications, vol. 9, no. 11, 2018, https://doi.org/10.14569/IJACSA.2018.091107.

@article{Jayasuriya2018,
  title     = {Experimental Study on an Efficient Dengue Disease Management System},
  journal   = {International Journal of Advanced Computer Science and Applications},
  volume    = {9},
  number    = {11},
  year      = {2018},
  publisher = {The Science and Information Organization},
  author    = {J M.M.C Jayasuriya and G.K.K.T.Galappaththi and M.A.Dilupa Sampath and H.N.Nipunika and W.H. Rankothge},
  doi       = {10.14569/IJACSA.2018.091107},
  url       = {https://doi.org/10.14569/IJACSA.2018.091107}
}

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