| Yazarlar (3) |
Mahmut SARI
Kırşehir Ahi Evran Üniversitesi, Türkiye |
|
Savaş BAYRAM
Erciyes Üniversitesi, Türkiye |
|
Emrah AYDEMİR
Sakarya Üniversitesi, Türkiye |
| Özet |
| 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. |
| Anahtar Kelimeler |
| Makale Türü | Özgün Makale |
| Makale Alt Türü | SSCI, AHCI, SCI, SCI-Exp dergilerinde yayınlanan tam makale |
| Dergi Adı | Turkish Journal of Civil Engineering |
| Dergi ISSN | 2822-6836 Wos Dergi Scopus Dergi |
| Dergi Tarandığı Indeksler | SCI-E |
| Dergi Grubu | Q4 |
| Makale Dili | İngilizce |
| Basım Tarihi | 10-2025 |
| Cilt No | 37 |
| Sayı | 2 |
| Doi Numarası | 10.18400/tjce.1618975 |
| Makale Linki | https://doi.org/10.18400/tjce.1618975 |
| Atıf Sayıları |
