Leveraging Historical Data from Project Control Systems for Accurate Cost Estimation: A Machine Learning Perspective
Keywords:
Machine Learning, Cost Estimation, Project Management, Ensemble Techniques, Software Effort Estimation, Predictive Analytics, Resource Allocation, Financial Planning.Abstract
In this paper, historical data from a project control software is utilised for analysis of the possibility that
machine learning models can improve the precision of cost estimation. Which individual and ensemble
techniques are appropriate for predicting project cost as well as effort in software development is determined
through this research, comparing individual and ensemble strategies.
Case studies and extensive reviews in the literature provide preliminary results showing that ensemble strategies
significantly raise the precision of prediction. This advance provides more better resource allocation, planning of
finance, and overall success for the project. This research study underlines that one needs to integrate advanced
models of machine learning into project management procedures in order to improve on decisions and reduce
risk.
