Estimating Highway Preconstruction Services Costs - Volume 2: Research Report (2016) / Chapter Skim
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34 C H A P T E R 4 4.1 Introduction This section presents the methodology followed to develop the data-driven PCS estimating models as described earlier (see Section 1.5, Task 4)
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35 Note: PS&E = plans, specifications, and estimates. Planning Programming Preliminary Design Final Design Need Assessment Public Involvement Hydraulic Study Right-of-way Acquisition Environmental Clearance Economic Feasibility PS & E Roadway Design Bridge Design Underground Utilities Surveying Schematic Development Traffic Control Plans Geotechnical Investigation Figure 4.1.
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36 The cost differences need to be documented and explained. For example, scope changes during the project development process would significantly affect the total PCS costs from the bottom-up estimating approach, resulting in a significant deviation from the top-down PCS cost estimate.
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37 tion of the procedure associated with the development and optimization of a PCS database. Some of the strategies in this chapter are intended to minimize data management efforts while still producing reliable PCS cost estimates.
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38 Table 4.1. Potential factors affecting PCS costs.
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39 own values for various factors. For example, project type classification for the Iowa DOT may vary from that of the Montana DOT.
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Note: PCC = Portland cement concrete, HMA = hot-mix asphalt, RCB = reinforced concrete bridge. Figure 4.4.
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41 4.6.2 Data Cleaning and Transforming Data quality is one of the main issues confronted when developing a data-driven model. It is possible that some of the data attributes may have a significant number of missing values.
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42 4.7 Develop/Update PCS Database Once the potential set of input variables has been defined for PCS cost-estimating modeling, the agency can proceed with the development of the PCS database. As discussed earlier in this chapter, there are different PCS cost-estimating approaches (top-down and bottom-up/functional level)
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43 The size of a PCS database is defined by the number of potential input variables and the amount of historical data for each of those variables (illustrated in Figure 4.7)
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44 Along with the experience of model developers, there are formal methods that may help to evaluate the influence of factors before proceeding to the development of estimating models. Descriptive statistics and visualization techniques, such as scatter plots and box plots, can provide a better understanding of the data and their relationship to PCS costs.
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45 regression cannot use nominal variables as input variables. Nominal variables are categorical variables that are not ordered.
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46 The model can be optimized by using a cyclic process intended to discard, one by one, those independent variables that do not show a statistically significant impact on final PCS costs (P-value > 0.05)
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47 An example of multiple regression is provided within the guidebook in Section 4.2.1. 4.8.2 Decision Tree A decision tree identifies projects with similar characteristics and identifies more important cost influencers and presents them in a visual way.
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48 In addition to the measures in Table 4.4, the minimum and maximum errors can also be used to check the accuracy of the model. When developing a decision tree, the factors affecting PCS costs can be selected based on attribute evaluation techniques such as subset evaluation and principal component analysis.
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49 nation of the variables with less and high importance may provide better accuracy than the combination of the highimportance variables only. As such, various combinations of variables should be tried.
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50 remaining 33% of data points are used to test the accuracy of the model. In k-fold cross validation, usually 10-fold, the data set is partitioned into k-folds (say 10 parts)
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51 in management's decision on whether to perform the work with in-house resources. If the estimated work effort does not require specialized services and can be accommodated into the department's schedule, then a decision to do the work inhouse can be made.
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52 The most probable number of work-effort hours required for the task of utility coordination and documentation is 15 (after rounding up from 14.5)
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53 At the Model Level The following KPIs are used to measure the overall performance of the PCS cost-estimating model. In order to draw any conclusions or take any corrective actions to improve preconstruction practices or the performance of the model, the agency should analyze the following three KPIs obtained from the application of the model in a series of projects.
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54 People Description Questions in this category should relate to team effectiveness and stakeholder interactions. Sample questions include those in the next cell.
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