Guess the time of implementation of residential construction projects using neural networks ANN Elaf Dheyaa Abdulridha AL-Zubaidi, Ali Hashim Yas, Hayder Fadhil Abbas Periodicals of Engineering and Natural Sciences, 2019 The construction duration of residential projects, especially in building processes, significantly impact the business of a construction company. The balance between the planned cost, direct cost, and overheads directly depend on the precision of the implementation phase of the project. The application of the artificial neural network (ANN) to predict the duration of implementation of a residential construction project from the pre-design stage to completion is comprehensively discussed in this research. The study applies the back-propagation (BP) network made of nodes for error evaluation of the training states. Further, the proposed system illustrated that the artificial neural network (ANN) satisfy the three crucial criteria (cost, quality, and time) used for the evaluation of projects. The ANN provided accurate data for the training and estimation of, the duration of a residential construction project with adequate resources of implementation. The performance of the results for the ANN at 105 iteration shows that the prediction was 99.841% accurate for the overall system. The best fit occurred at the 99th epoch with an MSE of 0.10286.
Project management information system effect decision making in the construction industry of Iraq Periodicals of Engineering and Natural Sciences, 2019
