Abstract
The area of time series analysis is an active research area in the last couple of years. This analysis is primarily used in various domains like forecasting the weather, prediction of earthquakes, processing the signals, communication engineering and related domains involving any temporal measurements. The above said domains bring up an important challenge, making it to develop new methods or solutions to predict them with good accuracy or classify them using machine learning. In this paper, we present the infant mortality rate in India to accurately predict with the help of window-based ARIMA models with best tuning parameters which are determined. The experimental results show that by 2023, the death rate is going to be almost zero for 1000 life people in India. Furthermore, it provides an analysis of the notion and tools for time series analysis.
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Jagan Mohan Reddy, D., Basha, S.J. (2021). Analysis of Infant Mortality Rate in India Using Time Series Analytics. In: Singh Pundir, A.K., Yadav, A., Das, S. (eds) Recent Trends in Communication and Intelligent Systems. Algorithms for Intelligent Systems. Springer, Singapore. https://doi.org/10.1007/978-981-16-0167-5_8
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DOI: https://doi.org/10.1007/978-981-16-0167-5_8
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