A Review of the Application of Decision Tree Analysis and Artificial Neural Networks in Project Management

Olusina Temidayo Akinyokun, Onifade. Morakinyo Kehinde, Adegoke Michael Abejide

Abstract


The advancement of computing and communication technologies has fueled the growth of Information Technology (IT), with Artificial Intelligence (AI) emerging as a transformative force in modernizing project management practices. This study explores the application of two prominent AI techniques—Decision Tree Analysis (DTA) and Artificial Neural Networks (ANN)—in improving project planning and control. A review of empirical studies highlights the limitations of conventional tools such as Gantt charts and the Critical Path Method (CPM) in managing complex project variables, often resulting in cost overruns and schedule delays. In contrast, DTA and ANN demonstrate superior predictive accuracy, decision support, and adaptability capabilities. DTA offers transparent and structured decision-making models, while ANN excels in pattern recognition and outcome forecasting. The findings underscore that integrating these AI tools enhances project efficiency, cost estimation, and time management, establishing AI as a critical asset for future project success.

Keywords: Artificial Intelligence, Decision Tree Analysis, Artificial Neural Networks, Project Planning, Project Control


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References


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DOI: http://dx.doi.org/10.24014/jti.v11i1.16480

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