@article{zaychenko2024hybrid,
  title     = {A Hybrid Model of Artificial Intelligence Integrated into GIS for Predicting Accidents in Water Supply Networks},
  author    = {Zaychenko, Yuriy and Starovoit, Tetiana},
  journal   = {System Research and Information Technologies},
  year      = {2024},
  volume    = {2},
  number    = {},
  pages     = {xx--yy},
  doi       = {10.20535/SRIT.2308-8893.2024.2.04},
  url       = {https://doi.org/10.20535/SRIT.2308-8893.2024.2.04},
  issn      = {2308-8893},
  abstract  = {This study presents a hybrid AI model based on ANFIS enhanced with genetic algorithms and ant colony optimization (ACO), integrated into a GIS for spatiotemporal prediction of accidents in urban water networks. The system was tested on real-world data from Kyiv, Ukraine. Forecast accuracy improved by up to 11%, making the approach promising for smart city utilities.},
  keywords  = {ANFIS, ACO, GA, spatial objects, geodatabase, metaheuristics, spatiotemporal analysis, water loss}
}