Estimating the Optimum Duration of Road Projects Using Neural Network Model
Atheer Mahmood Al-saadi, Salah Kh. Zamiem, Luma Ahmed Aday, Munqith JameelJubair, Heba Abdalla Al- Hashemi · International Journal of Engineering and Technology · 2017
The aim of this study to predictedthe duration of road projects in republic of Iraq.Historical data was adopted for ( 99) projects for interval between 2000 to 2017 from Roads and Bridges Directorate (RBD).Artificial Neural Network (ANN)model used to estimate the duration usingsix variables (length of road, No.of lane, No.of intersection, volume of earth, type of pavement and furniture level).The methodology used in this study included two important parts, the first part, reviewing the literature of the subject (estimating the duration of the road projects), and the second part, used of a program neuframe v.4 to build the models of neural networks to estimate the duration of road project.The results showed strong correlation between actual duration and predict duration by (90.6%), minimizes testing error (3.2%) and training error (4.9%).The MAPE and Average Accuracy Percentage generated by ANN model were found to be(25.73 %) and(74.27%)respectively.Therefore, it can be concluded that ANNs model show very good agreement with the actual measurements.