Muhammad Bilal's Outputs (7)

Predicting completion risk in PPP projects using big data analytics (2018)
Journal Article

Accurate prediction of potential delays in public private partnerships (PPP) projects could provide valuable information relevant for planning and mitigating completion risk in future PPP projects. However, existing techniques for evaluating completi... Read More about Predicting completion risk in PPP projects using big data analytics.

Reusability analytics tool for end-of-life assessment of building materials in a circular economy (2018)
Journal Article

Purpose – In a circular economy, the goal is to keep materials values in the economy for as long as possible. For the construction industry to support the goal of the circular economy, there is the need for materials reuse. However, there is little o... Read More about Reusability analytics tool for end-of-life assessment of building materials in a circular economy.

Big data platform for health and safety accident prediction (2018)
Journal Article

Purpose – The purpose of this paper is to highlight the use of the big data technologies for health and safety risks analytics in the power infrastructure domain with large data sets of health and safety risks, which are usually sparse and noisy. Des... Read More about Big data platform for health and safety accident prediction.

Public private partnerships (PPP) in the developing world: Mitigating financiers’ risks (2018)
Journal Article

Purpose – A major challenge for foreign lenders in financing public private partnerships (PPP) infrastructure projects in an emerging market (EM) is the bankability of country-related risks. Despite existing studies on country risks in international... Read More about Public private partnerships (PPP) in the developing world: Mitigating financiers’ risks.

A Big Data analytics approach for construction firms failure prediction models (2018)
Journal Article

Using 693,000 datacells from 33,000 sample construction firms that operated or failed between 2008 and 2017, failure prediction models were developed using artificial neural network (ANN), support vector machine (SVM), multiple discriminant analysis... Read More about A Big Data analytics approach for construction firms failure prediction models.

Designing out construction waste using BIM technology: Stakeholders’ expectations for industry deployment (2018)
Journal Article

© 2018 The Authors The need to use Building Information Modelling (BIM) for Construction and Demolition Waste (CDW) minimisation is well documented but most of the existing CDW management tools still lack BIM functionality. This study therefore asses... Read More about Designing out construction waste using BIM technology: Stakeholders’ expectations for industry deployment.

A framework for big data analytics approach to failure prediction of construction firms (2018)
Journal Article

This study explored use of big data analytics (BDA) to analyse data of a large number of construction firms to develop a construction business failure prediction model (CB-FPM). Careful analysis of literature revealed financial ratios as the best for... Read More about A framework for big data analytics approach to failure prediction of construction firms.