Dataset is taken from https://archive.ics.uci.edu/ml/datasets/Alcohol+QCM+Sensor+Dataset:
M. Fatih Adak, Peter Lieberzeit, Purim Jarujamrus, Nejat Yumusak, Classification of alcohols obtained by QCM sensors with different characteristics using ABC based neural network, Engineering Science and Technology, an International Journal, 2019,ISSN 2215-0986
Data Set Information:
In the dataset there are 5 types of dataset. QCM3, QCM6, QCM7, QCM10, QCM12
In each of dataset, There is alcohol classification of five types, 1-octanol, 1-propanol, 2-butanol, 2-propanol, 1-isobutanol
In this study, five different QCM gas sensors are used, and five different gas measurements (1-octanol, 1-propanol, 2-butanol, 2- propanol and 1-isobutanol) are conducted in each of these sensors.
The gas sample is passed through the sensor in five different concentrations.
These concentrations are: Concentration Air ratio (ml) Gas ratio (ml)
- 1 0.799 0.201
- 2 0.700 0.300
- 3 0.600 0.400
- 4 0.501 0.499
- 5 0.400 0.600
There are two different channels in these QCM sensors. One of these channel includes molecularly imprinted polymers (MIP), and the other includes nanoparticles (NP). Diverse QCM sensor structures are obtained using different MIP and NP ratios. MIP and MP ratios used in the QCM sensors are:
Sensor name MIP : NP ratio
- QCM3 1 : 1
- QCM6 1 : 0
- QCM7 1 : 0.5
- QCM10 1 : 2
- QCM12 0 : 1
- alcohol_single.ipynb - testing single sensors
- alcohol_pairs.ipynb - testing of a pair sensor