Applying Neural Networks and Analogous Estimating to Determine the Project Budget

This paper aims to discuss the use of the Artificial Neural Networks (ANN) to model aspects of the project budget where traditional algorithms and formulas are not available or not easy to apply. Neural networks use a process analogous to the human brain, where a training component takes place with existing data and subsequently, a trained neural network becomes an “expert” in the category of information it has been given to analyse. This “expert” can then be used to provide projections given new situations based on an adaptive learning.

Modelling Line of Balance Schedules with Start-Finish Relationships

The use of the Line of Balance Scheduling Method has been increasing, especially on the construction industry companies of Brazil, Finland and Australia. The method addresses to the particularities of construction projects more effectively than the Critical Path Method does. In order to model the schedule, the paper demonstrates the “start-finish” relation and its contributions for the two approaches for the modelling: Network and Linear Scheduling Approach.

Determining the Mathematical ROI of a Project Management Office (PMO) Implementation

The objective of this paper is to present, discuss and apply a mathematical model based on the use of Monte Carlo simulation in conjunction with researches on project success/failure rates of projects to develop a 10 step model to calculate the mathematical return on investment (ROI) for the Project Office implementation.

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