Hamza Al-bdour

Within the complex domain of construction project management, the accurate anticipation of time overruns is a significant obstacle, particularly within the specific context of the construction sector in Jordan. This study aimed to utilize deep learning, specifically the Multi-Layer Perceptron (MLP), and enhance its overrun predictive ability by inc...

Within the dynamic field of modern architecture and infrastructure, the concept of intelligent building adaptation arises as a fundamental element in attaining both energy efficiency and the highest level of comfort for occupants. The difficult task of occupancy prediction is crucial to the overall adaptability. The present study presents a unique...

This study compares Bayesian Optimization-based machine learning systems that anticipate earthquake-damaged buildings and to evaluates building damage classification models. Using metrics, this study evaluates Random Forest, ElasticNet, and Decision Tree algorithms. This study showed damage level asymmetry. Fifth grade is the most prevalent and fir...

The objective of this research is to find out more about where and how architects get their ideas, as well as what role those ideas play in the design process. In this study, 32 students in their fourth year of architectural engineering at Al-Balqa Applied University were surveyed using a quantitative (questionnaire survey) analytical method....

This study focuses on optimizing soil settlement and consolidation prediction in Finland clays using machine-learning regressions with Bayesian hyperparameter selection. Specifically, the study aims to predict the pre-consolidation stress (sp) using an Extra Trees Regressor (ETR) model. Root mean square error (RMSE) was used as a performance metric...

This research provides evidence of well-established evaluation frameworks for predicting time and cost overruns. There have been several attempts to reduce this issue, but these overruns still harm the construction industry worldwide. To create hyper-parameter-optimized predictive models, the numerical data was primarily used to train a specific ty...

Cost and time overruns are currently posing a worldwide challenge to completing construction projects. Previous research looked at the factors that contributed to schedule and expense overruns to find a solution. Machine learning (ML) strategies have been successfully applied in a wide range of research fields to extract novel and important informa...