Computer-based fuzzy logic for forecasting the population census of Edo State, Nigeria

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.