• Title of article

    Prediction Missiles Attacks on the War with Machine Learning

  • Author/Authors

    Khanchoupan ، Milad Department of Chemical Engineering - Imam Hossein University , Bahramizadeh ، Amirhossein Department of Computer Science - Sadjad University , Garoosi ، Hamed Department of Electrical Engineering - Babol Noshirvani University of Technology

  • From page
    48
  • To page
    58
  • Abstract
    This paper aims to explore using machine learning to predict potential missile attacks on other country. With the escalating tensions between the two countries, there is a need to develop predictive models that can forecast missile strikes and provide early warnings. The research will focus on leveraging historical data, geopolitical factors, and patterns of past attacks to train machine learning algorithms for this purpose. The goal is to create a predictive model that can assist decision-makers in taking proactive measures to mitigate the impact of such attacks. Additionally, the study will address the ethical considerations and challenges involved in using machine learning for sensitive military predictions.
  • Keywords
    Missiles , War conflict , Prediction , Machine learning
  • Journal title
    International journal of industrial engineering and operational research
  • Journal title
    International journal of industrial engineering and operational research
  • Record number

    2765328