List of Tables

Table 1.1 Relevant studies and publications
Table 2.1 Structure of analysed operating costs
Table 2.2 Predictor variable groups
Table 3.1 Operating cost indicators
Table 3.2 Qualitative candidate predictor variable type of facility
Table 3.3 Comparison of the total, test, and training samples
Table 4.1 Absolute cost models of CG 300
Table 4.2 Cost indicator models of CG 300
Table 4.3 Coefficients of non-linear regression model NLR(ind)300
Table 4.4 Specifications of binary classification tree model BCT(ind)300
Table 4.5 Categorised CG 300 cost indicators
Table 4.6 Comparison of PE and MAPE of CG 300
Table 4.7 Absolute cost models of CG 310
Table 4.8 Cost indicator models of CG 310
Table 4.9 Coefficients of non-linear regression model NLR(ind)310
Table 4.10 Specifications of binary classification tree model BCT(ind)310
Table 4.11 Categorised CG 310 cost indicators
Table 4.12 Comparison of PE and MAPE of CG 310
Table 4.13 Absolute cost models of CG 311
Table 4.14 Cost indicator models of CG 311
Table 4.15 Coefficients of non-linear regression model NLR(ind)311
Table 4.16 Specifications of binary classification tree model BCT(ind)311
Table 4.17 Categorised CG 311 cost indicators
Table 4.18 Comparison of PE and MAPE of CG 311
Table 4.19 Absolute cost models of CG 312-316
Table 4.20 Cost indicator models of CG 312-316
Table 4.21 Coefficients of non-linear regression model NLR(ind)312-316
Table 4.22 Specifications of binary classification tree model BCT(ind)312-316
Table 4.23 Categorised CG 312-316 cost indicators
Table 4.24 Comparison of PE and MAPE of CG 312-316
Table 4.25 Absolute cost models of CG 316
Table 4.26 Cost indicator models of CG 316
Table 4.27 Coefficients of non-linear regression model NLR(ind)316
Table 4.28 Specifications of binary classification tree model BCT(ind)316
Table 4.29 Categorised CG 316 cost indicators
Table 4.30 Comparison of PE and MAPE of CG 316
Table 4.31 Absolute cost models of CG 320
Table 4.32 Cost indicator models of CG 320
Table 4.33 Coefficients of non-linear regression model NLR(ind)320
Table 4.34 Specifications of binary classification tree model BCT(ind)320
Table 4.35 Categorised CG 320 cost indicators
Table 4.36 Comparison of PE and MAPE of CG 320
Table 4.37 Absolute cost models of CG 330
Table 4.38 Cost indicator models of CG 330
Table 4.39 Coefficients of non-linear regression model NLR(ind)330
Table 4.40 Specifications of binary classification tree model BCT(ind)330
Table 4.41 Categorised CG 330 cost indicators
Table 4.42 Comparison of PE and MAPE of CG 330
Table 4.43 Absolute cost models of CG 340
Table 4.44 Cost indicator models of CG 340
Table 4.45 Coefficients of non-linear regression model NLR(ind)340
Table 4.46 Specifications of binary classification tree model BCT(ind)340
Table 4.47 Categorised CG 340 cost indicators
Table 4.48 Comparison of PE and MAPE of CG 340
Table 4.49 Absolute cost models of CG 350
Table 4.50 Cost indicator models of CG 350
Table 4.51 Coefficients of non-linear regression model NLR(ind)350
Table 4.52 Specifications of binary classification tree model BCT(ind)350
Table 4.53 Categorised CG 350 cost indicators
Table 4.54 Comparison of PE and MAPE of CG 350
Table 4.55 Absolute cost models of CG 352
Table 4.56 Cost indicator models of CG 352
Table 4.57 Coefficients of non-linear regression model NLR(ind)352
Table 4.58 Specifications of binary classification tree model BCT(ind)352
Table 4.59 Categorised CG 352 cost indicators
Table 4.60 Comparison of PE and MAPE of CG 352
Table 4.61 Absolute cost models of CG 353
Table 4.62 Cost indicator models of CG 353
Table 4.63 Coefficients of non-linear regression model NLR(ind)353
Table 4.64 Specifications of binary classification tree model BCT(ind)353
Table 4.65 Categorised CG 353 cost indicators
Table 4.66 Comparison of PE and MAPE of CG 353
Table 4.67 Absolute cost models of CG 354
Table 4.68 Cost indicator models of CG 354
Table 4.69 Coefficients of non-linear regression model NLR(ind)354
Table 4.70 Specifications of binary classification tree model BCT(ind)354
Table 4.71 Categorised CG 354 cost indicators
Table 4.72 Comparison of PE and MAPE of CG 354
Table 4.73 Absolute cost models of CG 355
Table 4.74 Cost indicator models of CG 355
Table 4.75 Coefficients of non-linear regression model NLR(ind)355
Table 4.76 Specifications of binary classification tree model BCT(ind)355
Table 4.77 Categorised CG 355 cost indicators
Table 4.78 Comparison of PE and MAPE of CG 355
Table 4.79 Absolute cost models of CG 360
Table 4.80 Cost indicator models of CG 360
Table 4.81 Coefficients of non-linear regression model NLR(ind)360
Table 4.82 Specifications of binary classification tree model BCT(ind)360
Table 4.83 Categorised CG 360 cost indicators
Table 4.84 Comparison of PE and MAPE of CG 360
Table 4.85 Absolute cost models of CG 370
Table 4.86 Cost indicator models of CG 370
Table 4.87 Coefficients of non-linear regression model NLR(ind)370
Table 4.88 Specifications of binary classification tree model BCT(ind)370
Table 4.89 Categorised CG 370 cost indicators
Table 4.90 Comparison of PE and MAPE of CG 370
Table 5.1 Identified reference quantities
Table 5.2 Identified predictor variables (Quantities)
Table 5.3 Identified predictor variables (Characteristics)
Table 5.4 Identified predictor variables (Utilisation, location, strategy)
Table 5.5 Comparison of MAPE for developed statistical methods
Table 5.6 Comparison of MAPE for 1st, 2nd, and 3rd level cost estimation
Table 6.1 Implementation of categorised CG 370 cost indicators
Table 6.2 Observed and estimated values for example facility
Table 6.3 PE and MAPE for example facility
Table A.1 Absolute operating costs
Table A.2 Percentage distribution on 1st level operating costs
Table A.3 Percentage distribution on 2nd level operating costs
Table A.4 Operating cost indicators
Table A.5 Candidate reference quantities
Table A.6 Candidate predictor variables: Specific areas
Table A.7 Candidate predictor variables: Compactness
Table A.8 Candidate predictor variables: Function
Table A.9 Candidate predictor variables: Condition
Table A.10 Candidate predictor variables: Standard
Table A.11 Candidate predictor variables: Location
Table A.12 Candidate predictor variables: Utilisation
Table A.13 Candidate predictor variables: Management strategy
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