MACHINE LEARNING-BASED APPROACH TO FORECASTING THE DEGREE OF URBANIZATION
Journal Title: International scientific journal Science and Innovation - Year 2024, Vol 3, Issue 7
Abstract
This article examines the application of machine learning methods for predicting the level of urbanization in Samarkand region. Based on data from the State Statistics Committee of the Republic of Uzbekistan, a comprehensive database including 25 key factors was developed. The study employed machine learning algorithms such as neural network, decision tree, and random forest. Results showed that the neural network model had the highest accuracy (RMSE = 0.44). Based on the obtained results, the advantages and limitations of machine learning methods in predicting urbanization processes were discussed. The research findings can serve as a valuable resource in urban development planning and shaping urbanization policies.
Authors and Affiliations
Ismailov I. T.
Keywords
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- EP ID EP744610
- DOI 10.5281/zenodo.13120693
- Views 51
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