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Efficacy of Artificial Neural Networks (ANN) as a Tool for Predictive Analytics

In: Analytics Enabled Decision Making

Author

Listed:
  • Deepti Sinha

    (CHRIST (Deemed to be University))

  • Pradeepta Kumar Sarangi

    (Chitkara University)

  • Sachin Sinha

    (CHRIST (Deemed to be University))

Abstract

ABSTRACT Predictive analytics could also be defined as the application of statistical techniques and mathematical modeling to anticipate the future performance and expected return on investments. Predictive analytics examines the most recent and the historical data to see if the same pattern is likely to reoccur or not. This gives an opportunity to businessmen and financial investors to make an appropriate decision about their investments and expected returns. Ever since the development of ANN technique, researchers have tried to create a number of predictive models using ANN. The chapter is focused on defining predictive analytics and the tools used in predictive analytics, with a special orientation on Artificial Neural Networks. The objective of the chapter is to establish ANN as an effective technique for making appropriate predictions and thereby contributing toward the decision-making in various spheres using the outcomes from various researches. The chapter also aims to explain the step-by-step process of ANN in outcome prediction with the help of example.

Suggested Citation

  • Deepti Sinha & Pradeepta Kumar Sarangi & Sachin Sinha, 2023. "Efficacy of Artificial Neural Networks (ANN) as a Tool for Predictive Analytics," Springer Books, in: Vinod Sharma & Chandan Maheshkar & Jeanne Poulose (ed.), Analytics Enabled Decision Making, pages 123-138, Springer.
    • Handle: RePEc:spr:sprchp:978-981-19-9658-0_6
    DOI: 10.1007/978-981-19-9658-0_6
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