Abstract
Although the National Population Commission's forecasting efforts have become more accurate over the years, this work aims to use fuzzy logic to predict population growth in a quicker, simpler, more accurate, and more effective way. To accomplish this goal, various data collection technologies were employed to compile data from secondary sources, including the National Population Commission of Nigeria. A thorough literature evaluation on population forecasts and censuses has already been published. Implementing a proactive population forecast was built with a stated goal in mind. Python 3 was chosen as a reliable programming language for ODEINT (Ordinary Differential Equation Integration) for Natural Growth Model and Fuzzy Time Series library functions. Due to a performance accuracy of 99.6%, the model created for population census forecasting projects the future population at a dependable time.
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