Table 1
Classification of the data validation methods by functionality.
| | Groups of data validation methods | Methods included | Description |
| | Faulty data detection methods | ANNs
(i) MLP; AANN; BP algorithm; SVM;
Instance based
(i) SOM
Gaussian distributions
Statistical methods
(i) ASV; HSV
Probabilistic methods
(i) Bayesian Networks; Propagation in Trees; Probabilistic Causal Methods; Learning Algorithms; Sparse Bayesian Learning; RVM; SPRT
Dimensionality Reduction
(i) Fuzzy logic; PCA; KPCA;
others
(i) Hybrid AANN-KPCA | Consisting of the detection of faulty or incorrect values discovered during the data acquisition and processing stages |
| | Data correction methods | Kalman filter
LPC
ARMA
(i) AR; MA; EMD
Nadaraya-Watson statistical estimator
Interpolation
Smoothing
Data mining techniques
Data reconciliation techniques | Consisting of the estimation of faulty or incorrect values obtained during the data acquisition and processing stages |
| | Other assisting techniques or tools | Checking of the status of the sensors
Checking of the duration after sensor maintenance
Data context classification
Calibration of measuring systems
Uncertainty consideration
Grey models
(i) GBM; dynamic uncertainty estimation of self-validating sensor
VRFV method | These are different approaches created for the correct validation of the data |
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