Knowledge Based System for Population Growth Prediction

Abstract

Projection techniques are commonly employed in mathematical, statistical, and stochastic machine learning models, which rely on randomly generated parameters. However, these models often fail to incorporate crucial and unique factors such as population growth rates and demographics. This study aims to utilize a knowledge-based simulation method that incorporates a machine learning model. Additionally, we will implement a data independent prediction model equation and a data-driven model equation to generate predicted values for the population growth in Nigeria. To enhance the accuracy and consistency of the predicted data, we will employ a Java algorithm optimizer. The resulting predicted data will be valuable for planning purposes and will help overcome the limitations of previous models.