A hybrid model of artificial intelligence integrated into GIS for predicting accidents in water supply networks
Вантажиться...
Дата
2024
Автори
Науковий керівник
Назва журналу
Номер ISSN
Назва тому
Видавець
КПІ ім. Ігоря Сікорського
Анотація
The search for an effective and reliable model for predicting accidents on water supply networks by determining their exact locations has always been important for effectively managing water distribution systems. This study, based on the adaptive neuro-fuzzy logical inference system (ANFIS) model, was developed to predict accidents in the city of Kyiv (Ukraine) water supply network. The ANFIS model was combined with genetic algorithms and swarm optimization (ACO) methods and integrated into a GIS to visualize results and determine locations. Forecasts were evaluated according to the following criteria: mean absolute error (MAE), root mean square error (RMSE), and coefficient of determination (R2 ). Depending on the amount and type of input data, ANFIS optimization with genetic algorithms and swarm optimization (ACO) can, on average, increase the accuracy of ANFIS predictions by 10.1% to 11%. The obtained results indicate that the developed hybrid model may be successfully applied to predict accidents on water supply networks.
Опис
Ключові слова
ANFIS, ACO, GA, spatial objects, geodatabase, metaheuristics, spatiotemporal analysis, water loss, геоінформаційні системи, просторові об’єкти, просторово-часовий аналіз, втрати води
Бібліографічний опис
Zaychenko, Yu. A hybrid model of artificial intelligence integrated into GIS for predicting accidents in water supply networks / Zaychenko Yu., Starovoit T. // Системні дослідження та інформаційні технології : міжнародний науково-технічний журнал. – 2024. – № 1. – С. 52-67. – Бібліогр.: 25 назв.