Proceedings of the 2016 5th International Conference on Advanced Materials and Computer Science

Markov-chain Based Lottery Analysis System in Mobile Cloud Computing

Authors
Yi He, Rong Fu, Yingqian Zhang, Shuai Wu, Xin Liu, Tian Yuan
Corresponding Author
Yi He
Available Online June 2016.
DOI
10.2991/icamcs-16.2016.32How to use a DOI?
Keywords
mobile cloud computing, Markov chain, lottery analysis and forecasting, transition matrix
Abstract

This paper makes use of Markov chain to establish predictive model and analyze the historical data of lottery based on technologies of mobile cloud computing and HTML5 in order to predict the number sets with high-winning probability during next issue. It is indicated in the actual application that the system is capable of offering lottery buyers the analysis and forecasting service of lottery information anytime and anywhere, while effectively narrowing the scope of lottery winning with some practical significance.

Copyright
© 2016, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Volume Title
Proceedings of the 2016 5th International Conference on Advanced Materials and Computer Science
Series
Advances in Engineering Research
Publication Date
June 2016
ISBN
978-94-6252-189-6
ISSN
2352-5401
DOI
10.2991/icamcs-16.2016.32How to use a DOI?
Copyright
© 2016, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - Yi He
AU  - Rong Fu
AU  - Yingqian Zhang
AU  - Shuai Wu
AU  - Xin Liu
AU  - Tian Yuan
PY  - 2016/06
DA  - 2016/06
TI  - Markov-chain Based Lottery Analysis System in Mobile Cloud Computing
BT  - Proceedings of the 2016 5th International Conference on Advanced Materials and Computer Science
PB  - Atlantis Press
SP  - 163
EP  - 166
SN  - 2352-5401
UR  - https://doi.org/10.2991/icamcs-16.2016.32
DO  - 10.2991/icamcs-16.2016.32
ID  - He2016/06
ER  -