On a 32-point water quality dataset from Durban, a quantum support vector classifier reached 75% accuracy while a quantum neural network consistently failed to train.
Eco- Environment & Health 1(2), 107–116 (2022)
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
quant-ph 1years
2024 1verdicts
REJECT 1representative citing papers
citing papers explorer
-
Predicting Water Quality using Quantum Machine Learning: The Case of the Umgeni Catchment (U20A) Study Region
On a 32-point water quality dataset from Durban, a quantum support vector classifier reached 75% accuracy while a quantum neural network consistently failed to train.