Predicting Dengue Using Fuzzy Association Rule Mining

  IJCTT-book-cover
 
International Journal of Computer Trends and Technology (IJCTT)          
 
© 2019 by IJCTT Journal
Volume-67 Issue-3
Year of Publication : 2019
Authors : Anitha A, Freeda Jebamalar S
  10.14445/22312803/IJCTT-V67I3P114

MLA

MLA Style: Anitha A, Freeda Jebamalar S, "Predicting Dengue Using Fuzzy Association Rule Mining" International Journal of Computer Trends and Technology 67.3 (2019): 72-74.

APA Style: Anitha A, Freeda Jebamalar S, (2019). Predicting Dengue Using Fuzzy Association Rule Mining. International Journal of Computer Trends and Technology, 67(3), 72-74.

Abstract
Dengue is a fast emerging pandemic prone and most dreadful disease spread all over the world. It is caused by Aedes aegypti and aedes albopictus mosquitoes. It is affect the tropical and subtropical countries. Mosquitoes act as a transmitter and the main viticm will be the human. It consists of four distinct serotypes(DEN-1,2,3,4).It may belong to the genus flavivirus [6].The main reason for the propagation of vector and pathogen because of changes occurred in globalization of travel and trade. Temperature and precipitation will play the important factor in dengue. In 2007 Intergovernmental panel on climate change prescribed and believed that the range of 1.5 and 3.5 people all over the world will face risk of dengue fever in 2080[7]. Classification will compare and analysis the accuracy level. In this research fuzzy association rule mining is used to predict the dengue in the earlier phase with the formation of association rule along with the prediction. It may helps in quick diagnosis and save the human life.

Reference
[1] N.A Husin,A Alharogi,N.Mustapha,H.Hamdan,U.A Husin ”Early self-diagnosis of dengue symptoms using fuzzy and data mining approach”,AIP Conference 2016 Sep, 2018.
[2] M.V.J Reddy, B.Kavitha ”Expert system to predict the type of fever using data mining techniques on medical databases”IJCSE,vol.3,Issue.09,Sep. 2015
[3] N.Iqbal,M.Islam”Machine learning for dengue outbreak prediction :An Outlook”IJACS,vol .8,no. 1,Jan-Feb. 2017,pp. 93-102
[4] K.Chaturvedi,R.Patel,D.K Swami”A fuzzy Inference approach for association rule
[5] Odii J.N,Onwuama T.U,Okpalla C.L,Ejem A,”Job scheduling system using fuzzy logic approach”IJCTT,vol.42.no.2,Dec 2016. mining”IOSR,vol.16,Issue.6,Nov-Dec.2014,pp.57-66.
[6] http://www.who.int/denguecontrol/monitoring/en/
[7] https://www.ncbi.nlm.nih.gov/pmc/srticles/pmc5583666/
[8] https://searchsqlserver.techtarget.com/efinition/data-mining

Keywords
Climate, Dengue, Pathogen, Prediction, Mining