id	author	title	date	pages	extension	mime	words	sentence	flesch	summary	cache	txt
easat-8654	Kuppili, Shubham ; Sheng, Victor ; Kunal, Kishore ; Murgadoss, R. ; Madeshwaren, Vairavel 	Efficient AI-based water quality prediction and classification for sustainable urban environments in Texas city	2025	14	.pdf	application/pdf	6740	318	43	The study aims to analyze water pollution in Texas City using advanced AI methodologies, develop the EAI-WQP model for accurate forecasting of water quality parameters, implement real-time big data processing with Apache Spark, optimize model performance using the Firefly Algorithm (FA), classify water quality using ANFIS, and demonstrate the model's superiority over traditional machine learning methods. The creation and use of smart sensors for ongoing surveillance is covered, as well as how big data analytics improve the management and interpretation of water quality data.	cache/easat-8654.pdf	txt/easat-8654.txt