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Reseach Article

Election Result Prediction System using Hidden Markov Model [HMM]

by Mohd. Manjur Alam, Md. MezbahUddin, Shamsun Nahar Shoma
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 129 - Number 3
Year of Publication: 2015
Authors: Mohd. Manjur Alam, Md. MezbahUddin, Shamsun Nahar Shoma
10.5120/ijca2015906774

Mohd. Manjur Alam, Md. MezbahUddin, Shamsun Nahar Shoma . Election Result Prediction System using Hidden Markov Model [HMM]. International Journal of Computer Applications. 129, 3 ( November 2015), 1-4. DOI=10.5120/ijca2015906774

@article{ 10.5120/ijca2015906774,
author = { Mohd. Manjur Alam, Md. MezbahUddin, Shamsun Nahar Shoma },
title = { Election Result Prediction System using Hidden Markov Model [HMM] },
journal = { International Journal of Computer Applications },
issue_date = { November 2015 },
volume = { 129 },
number = { 3 },
month = { November },
year = { 2015 },
issn = { 0975-8887 },
pages = { 1-4 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume129/number3/23050-2015906774/ },
doi = { 10.5120/ijca2015906774 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T23:22:22.638303+05:30
%A Mohd. Manjur Alam
%A Md. MezbahUddin
%A Shamsun Nahar Shoma
%T Election Result Prediction System using Hidden Markov Model [HMM]
%J International Journal of Computer Applications
%@ 0975-8887
%V 129
%N 3
%P 1-4
%D 2015
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Election is an important part of political and social science. It can be defined in the field of Game as the winning chance of a team and TV reality show where candidates are the participants and decide if the participants will stay or not based on public votes. The election result can be predicted before the actual outcome using a prediction method. There are many methods, theory, and research to predict election result. Election prediction is very significant for the candidates and the society. It is normally based on some factors such as numbers of years in active politics, Popularity, Vote Bank, Development performance, Currently in Govt., View of voters towards party, Major Issue, Party/Independent and Internal War. In this paper a most famous model named Hidden Markov Model has been used to predict the results using these parameters.

References
  1. Text Dependent Speaker Identification using Hidden Markchov Model and Mel Frequency Cepstrum Coefficient,Mohd. ManjurAlam, Md. Salah UddinChowdury, NiazUddin Mahmud, BGC Trust University Bangladesh, International Journal of Computer Applications (0975 – 8887) Volume 104 – No.14, October 2014.
  2. Using voter-choice modeling to plan the final campaign in runoff elections, Wagner A. Kamakura, Rice University.
  3. Election Results Prediction System based on Fuzzy Logic, Harmanjit Singh Research Scholar, Singhania University,Rajasthan, INDIA Gurdev Singh, Ph.D Professor, Deptt of Information& Technology, Gurukul Vidyapeeth Institute of Engineering & Technology Banur, Chandigarh, Nitin Bhatia DAV College, Jalandhar Punjab, INDIA. International Journal of Computer Applications ((0975 – 8887) Volume 53– No.9, September 201214.
  4. Text-Independent Speaker Identification Using Hidden Markov Model SayedJaaferAbdallah, Izzeldin Mohamed Osman, Mohamed Elhafiz Mustafa, College of Computer Science and Information Technology Sudan University of Science and Techn, ogy, “World of Computer Science and Information Technology Journal (WCSIT) ISSN: 2221-0741 Vol. 2, No. 6, 203-208, 2012 Khartoum, Sudan.
  5. Predicting Election Popularity of a Person Using Crowd Sensing In Social Networks, Bangladesh. Mashroora Nadi,
  6. Syed Washfi Ahmad, S.M. Saquib Rahman, Brac University.
  7. Tumasjan, A., Sprenger, T., Sandner, P., & Welpe, I. (n.d.). Predicting Elections with Twitter: What 140 Characters Reveal about Political Sentiment.
  8. McCarthy, Colm and Terence M. Ryan (1977) “Estimates of Voter Transition Probabilities from the British General Elections of 1974,” Journal of the Royal Statistical Society. Series A, 140(1).
Index Terms

Computer Science
Information Sciences

Keywords

Hidden Markov Model (HMM) Election Commission of Bangladesh [ECB].