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Demographic Analysis of World Population Using Various Predictive Algorithms

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Micro-Electronics and Telecommunication Engineering

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 106))

Abstract

This project describes, in detail, the different regression models used in the analysis of population on various parameters like HDI, GDP, energy consumption and Internet usage. Population analysis can be useful in providing demographics of an area, help in targeted marketing and also help government to identify the areas of weakness of a country. Here, we have taken major countries and their various parameters like HDI, GDP, etc., and applied the regression models on them to find the most suitable one.

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References

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Author information

Authors and Affiliations

  1. Computer Science and Engineering, Amity School of Engineering & Technology, Amity University, Noida, Uttar Pradesh, 201303, India

    Ishan Bhatt & Kartik Ramaswamy

Authors
  1. Ishan Bhatt
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  2. Kartik Ramaswamy
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Corresponding author

Correspondence to Ishan Bhatt .

Editor information

Editors and Affiliations

  1. Department of Electronics and Communication Engineering, SRM Institute of Science and Technology, Delhi NCR Campus, Ghaziabad, India

    Devendra Kumar Sharma

  2. Department of Automatics and Applied Software, “Aurel Vlaicu” University of Arad, Arad, Romania

    Valentina Emilia Balas

  3. Department of Multimedia and Virtual Reality, Institute of Information Technology, Vietnam National University, Hanoi, Vietnam

    Le Hoang Son

  4. Department of Electronics and Communication Engineering, SRM Institute of Science and Technology, Delhi NCR Campus, Ghaziabad, India

    Rohit Sharma

  5. Department of Electrical and Electronics Engineering, Trakya University, Edirne, Turkey

    Korhan Cengiz

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Bhatt, I., Ramaswamy, K. (2020). Demographic Analysis of World Population Using Various Predictive Algorithms. In: Sharma, D.K., Balas, V.E., Son, L.H., Sharma, R., Cengiz, K. (eds) Micro-Electronics and Telecommunication Engineering. Lecture Notes in Networks and Systems, vol 106. Springer, Singapore. https://doi.org/10.1007/978-981-15-2329-8_23

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  • DOI: https://doi.org/10.1007/978-981-15-2329-8_23

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-15-2328-1

  • Online ISBN: 978-981-15-2329-8

  • eBook Packages: EngineeringEngineering (R0)

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