Work

Early Prediction of Construction Disputes: Decision Support Systems with Machine Learning Techniques

Year: 2025

Type: article

Abstract: This study aims to predict the outcomes of construction disputes before they proceed to litigation and to foster a constructive environment between parties. Within the scope of the study, a total of 24 legal factors; 14 legal factors were identified through extensive literature review and 10 legal factors were identified through content analysis. These legal factors were used in three stages: Pre-Litigation (A, B) and Post-Litigation. Legal factors with significant relationships were tested with 24 different machine learning algorithms. NB Tree, Logit Boost and LMT algorithms achieved 63.79%, 63.66% and 86.90% accuracy for models A, B and C, respectively.

Source: Turkish Journal of Civil Engineering

DOI: 10.18400/tjce.1618975

Authors: Mahmut Sarı, Savaş Bayram, Emrah Aydemir

Institutions: Ahi Evran University, Erciyes University, Sakarya University

Language: English

Topic: Artificial Intelligence in Law

Subfield: Political Science and International Relations

Field: Social Sciences

Domain: Social Sciences

SDG: Peace, justice, and strong institutions

Open Access status: diamond

Funder: Türkiye Bilimsel ve Teknolojik Araştırma Kurumu