Predictive Analysis of Lottery Outcomes Using Deep Learning and Time Series Analysis

International Journal of Engineering and Information Systems (IJEAIS) 7 (10):1-6 (2023)
  Copy   BIBTEX

Abstract

Abstract: Lotteries have long been a source of fascination and intrigue, offering the tantalizing prospect of unexpected fortunes. In this research paper, we delve into the world of lottery predictions, employing cutting-edge AI techniques to unlock the secrets of lottery outcomes. Our dataset, obtained from Kaggle, comprises historical lottery draws, and our goal is to develop predictive models that can anticipate future winning numbers. This study explores the use of deep learning and time series analysis to achieve this elusive feat. Through rigorous experimentation and data-driven approaches, we seek to determine the viability of AI in the realm of lottery predictions. Our findings reveal both the promise and limitations of AI in this context, shedding light on the complexities of lottery data and the potential need for quantum computing as a last resort.

Author's Profile

Samy S. Abu-Naser
North Dakota State University (PhD)

Analytics

Added to PP
2023-11-11

Downloads
958 (#13,349)

6 months
958 (#1,095)

Historical graph of downloads since first upload
This graph includes both downloads from PhilArchive and clicks on external links on PhilPapers.
How can I increase my downloads?