Spatial Correlation and Poverty Prediction Index (PPI) Generation Using Artificial Intelligence

Spatial Correlation and Poverty Prediction Index (PPI) Generation Using Artificial Intelligence examines computational approaches for analyzing spatial relationships and generating poverty prediction indicators through artificial intelligence. The book introduces spatial correlation, socioeconomic data analysis, predictive modeling, machine learning, and geographic data analysis. It considers how spatial patterns and related variables can be examined to identify relationships associated with poverty conditions and support prediction. Attention is given to data preparation, feature representation, spatial analysis, model development, prediction, and evaluation. The discussion connects artificial intelligence with poverty measurement and analytics, providing a foundation for socioeconomic assessment. The book is intended for students, researchers, data scientists, economists, and scientists interested in artificial intelligence, machine learning, spatial analysis, socioeconomic modeling.