## 4 Data--Analyses and Presentation  
As discussed in the previous section, data were collected for 135 severage construction projects. Data processing began with updates to severage construction costs, and Equation (1) was applied accordingly. The range of _UCC_ values is presented in Table 2, with costs provided in both CZK and EUR currencies. The table also includes the characteristics necessary for outlier analysis and elimination, namely, _Q1_, _Q3_, and _IQR_ values. Following the rule for outlier analysis elimination, as discussed in Section 2, the upper and lower boundaries for the range of values were computed in CZK \(<\)-3,435,919; 7,979,909\(>\) and in EUR \(<\)-144,792; 336,279\(>\). As the negative values of _UCC_ were not possible, these ranges were finally adopted--in CZK \(<\)0;7,979,909\(>\) and in EUR \(<\)0;336,279\(>\). _UCC_ values exceeding the upper boundary (and, consequently, entire records in the dataset, including values of cost predictors for relevant projects) were eliminated from further processing, analyses, and model development. After the removal of outliers, the dataset consisted of 125 records. Table 3 presents the descriptive statistics for _UCC_ values after outlier elimination. Comparing Tables 2 and 3, it is evident that the elimination of the 10 outliers from the dataset led to a significant narrowing of the _UCC_ value range. Consequently, high-cost projects, which were underrepresented in the dataset, were excluded from further data processing and model development. In accordance with the general assumptions for the development of the EoNN-based models, _UCC_ is assumed to be the dependent variable, denoted later as \(y\). Simultaneously, the pre-processing of cost predictors, which included data analysis, ordering, scaling, and coding, was carried out. The cost predictors were assigned to the set of independent variables, denoted as _xj_, as follows:  
* Type of a project: _x1_;
* Sewer pipe's length: _x2_;
* Type of Sewer pipe material: _x3_;
* Sewer pipe's diameter: _x4_; \begin{table}
\begin{tabular}{c c c} \hline \hline _UCC_ & \
\begin{tabular}{c} **CZK** \\ **(Thousands)** \\ \end{tabular} &
\begin{tabular}{c} **EUR 1** \\ **(Thousands)** \\ \end{tabular} \\ \hline Min & 247.08 & 10.41 \\ Max & 44,677.63 & 1882.75 \\ Range = max \(-\) min & 44,430.55 & 1872.34 \\ Average & 3458.49 & 145.74 \\
1 st quartile Q1 & 845.02 & 35.61 \\
3 rd quartile Q3 & 3698.97 & 155.88 \\ IQR & 2853.96 & 120.27 \\ \hline \hline \end{tabular} \({}^{\dagger}\)exchange rate according to the Czech National Bank for 30 June 2023 1 EUR = 23.730 CZK.  
\end{table} 
Table 2: Values range of contract costs for severage projects after the update. Characteristics of updated contract cost values distribution for outliers analysis and elimination. \begin{table}
\begin{tabular}{c c c} \hline \hline _UCC_ & \
\begin{tabular}{c} **CZK** \\ **(Thousands)** \\ \end{tabular} &
\begin{tabular}{c} **EUR 1** \\ **(Thousands)** \\ \end{tabular} \\ \hline Min & 247.08 & 10.41 \\ Max & 7531.92 & 317.40 \\ Range = max \(-\) min & 7284.85 & 306.99 \\ Average & 2130.52 & 89.78 \\ Median & 1522.22 & 64.14 \\ Standard deviation & 1792.95 & 75.56 \\ \hline \hline \end{tabular} \({}^{\dagger}\)exchange rate according to the Czech National Bank for 30 June 2023 1 EUR = 23.730 CZK.  
\end{table} 
Table 3: Descriptive statistics of updated contract cost values after outliers elimination. * Average depth of trench: \(x_{5}\);
* Groundwater table level: \(x_{6}\);
* Class of soil: \(x_{7}\);
* Number of manholes: \(x_{8}\);
* Number of crossings with other services: \(x_{9}\);
* Works on unpaved surface: \(x_{10}\);
* Works on paved surface: \(x_{11}\);
* Debris removal distance: \(x_{12}\). Descriptive statistics for cost predictors that originally had numerical values are presented in Table 4. These original numerical values were linearly scaled to the range <0.1, 0.9> for the purposes of computations and computer simulations of the artificial neural network (ANN).