Application of genetic algorithm and backpropagation neural networks to predict Tegal City population
DOI:
https://doi.org/10.35335/mandiri.v13i1.308Keywords:
Backpropagation, Genetic Algorithm, Prediction Models, Population, Tegal CityAbstract
Use of Genetic Algorithms and Backpropagation Neural Networks for Population Prediction in Tegal City, which aims to create precise prediction models using advanced computational techniques. This research uses a quantitative approach that combines experimental methods, data analysis, and model validation to implement and test predictive models. By using genetic algorithms for parameter optimization and neural network backpropagation for training, the findings show that the model can accurately predict population numbers with minimal error and high determination coefficients. The implications of this study are significant for urban planning and public policy development due to the accuracy and effectiveness of the model in forecasting population growth based on historical data.
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