Table 5 Methods combining error detection and correction (RQ2 and RQ3), along with its addressed errors, respective papers, and the total number of papers that proposed that method

Principal component analysis

Outliers, bias, drift, constant values, noise, stuck-at-zero

[46, 55]

2

Artificial neural network

Outliers, bias

[41, 43]

2

Bayesian network

Outliers, missing data

[7, 38]

2

Grey prediction model

Outliers, bias, constant values, stuck-at-zero

[30]

1

Dempster–Shafer theory

Uncertainty

[80]

1

Calibration-based method

Bias, drift, noise, stuck-at-zero

[73]

1

Hybrid methods

 Principal component analysis-based methods

Outliers, bias, drift, noise, constant values, stuck-at-zero

[60, 72, 74]

3

 Kalman filter-based methods

Outliers, bias, drift, missing data

[31, 51]

2

 Dempster–Shafer theory & Ontology

Uncertainty (inaccurate data), missing data (incomplete data)

[68]

1