水质
计算机科学
人工神经网络
质量(理念)
人工智能
机器学习
分类
数据挖掘
生态学
生物
认识论
哲学
作者
Talluru Tejaswi,Challapalli Manoj,Pepella Venkata Daivakeshwar Naidu,Tekkala Santhosh,Polaki Venkata Sai Akhil,Vithya Ganesan
标识
DOI:10.1109/icses55317.2022.9914054
摘要
Various contaminants, threatened water quality in recent years. Predicting and model construction for checking water quality have become crucial to control water pollution. Parameters such as water quality indexing (WQI) and water quality categorization has taken for measuring the level of quality. Artificial neural network models (ANN by NARNET and long short-term memory (LSTM) deep learning algorithm, usedto predict water quality indexing. For WQC forecasting, three machine learning techniques is applied to analysis seven water quality factors. Performance of Water quality estimation is compared in both NARAT and LSTM in terms of accuracy.
科研通智能强力驱动
Strongly Powered by AbleSci AI