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2017-Rosario-Antony-Mathematical Model for Future Population Scenario In India And China – An Econometric Approach

Author(s): Michael Rosario

NA

Keywords: logistic India vital coefficients Asia Carrying Vapacitiy annual growth rate

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Abstract

Resource Image A mathematical model including dynamical systems, statistical models and differential equations involves variety abstract structures. Population growth is one of the main issues in India and China which are located in Asia.

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Rosario, G. Michael and Dr. M. James Antony. 2017. Mathematical Model for Future Population Scenario In India And China – An Econometric Approach. International Journal of Scientific & Engineering Research. 8(5): 62-68. 

See https://www.ijser.org/researchpaper/Mathematical-Model-for-Future-Population-Scenario-In-India-And-China-An-Econometric-Approach.pdf . Accessed 29 March 2023.


Abstract: Mathematical modeling is a broad interdisciplinary science that uses mathematical and computational techniques to model and elucidate the phenomena arising in life sciences. A mathematical model including dynamical systems, statistical models and differential equations involves variety abstract structures. Population growth is one of the main issues in India and China which are located in Asia. These two countries are over populated and the growth in resources has not been keeping pace with the growth in population. So the increasing trend in population is great threat to the nations. The use of the logistic growth model is widely established in many fields of modeling and forecasting . In this paper, we will determine the carrying capacity and the vital coefficients governing the population growth of India and China. Further this study gives an insight on how to determine the carrying capacity and the vital coefficients, governing population growth, by using the least square method. Future Population growth rates and Global ranks of India and China are predicted.

Keywords: Logistic growth model, Carrying capacity, Vital coefficients, Annual growth rate.

 

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Author(s): Michael Rosario

NA

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