Monitoring of drinking-water quality by means of a multi-objective ensemble learning approach
Author:
Affiliation:
1. Pontifícia Universidade Católica do Paraná (PUCPR), Curitiba, Paraná, Brazil
Funder
Conselho Nacional de Desenvolvimento Científico e Tecnológico
Coordenação de Aperfeiçoamento de Pessoal de Nível Superior
Publisher
ACM
Link
https://dl.acm.org/doi/pdf/10.1145/3319619.3326745
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1. Evaluation of Machine Learning Algorithms on Finding Drinking Water Quality Based on Feature Selection Methodologies;2023 9th International Conference on Advanced Computing and Communication Systems (ICACCS);2023-03-17
2. Multi-criteria Decision-Making Techniques for the Selection of Pareto-optimal Machine Learning Models in a Drinking-Water Quality Monitoring Problem;International Journal of Information Technology & Decision Making;2023-02-13
3. Detecting Anomalies in Multidimensional Time Series Using Binary Classification;Communications in Computer and Information Science;2023
4. Accessing Imbalance Learning Using Dynamic Selection Approach in Water Quality Anomaly Detection;Symmetry;2021-05-07
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