Construction cost predictions to reduce time risk assessment are indispensable steps for
process of decision-making of managers. Machine learning techniques need adequate …

This study reviews the common practices and procedures conducted to identify the cost
drivers that the past literature has classified into two main categories: qualitative and …

In this study, it was investigated that how machine learning (ML) methods show performance
in different problems having different characteristics. Six ML approaches including Artificial …

Prognostic and health management (PHM) can ensure that a lithium-ion battery is working
safely and reliably. The main approach of PHM evaluation of the battery is to determine the …

The success of construction projects is a fundamental issue for most governments, users
and communities. In the literature that deals with construction project success and causes of …

While a growing body of literature focuses in detecting and analyzing the main reasons
affecting project success, the use of these results in project portfolio management is still …

The construction industry is a very competitive high-risk business. Many problems, such as
little cooperation, lack of trust, and ineffective communication resulting in adversarial …

In an age of depleting earth due to global warming impacting badly on the ozone layer of the
earth system, the need to employ technologies to substitute those engineering practices …

In a globally competitive world, with diminishing profit margins and decreasing market
shares, the cost of a project is one of the major criteria in decision making at the early stages …

This paper aims to establish, train, validate, and test artificial neural network (ANN) models
for modelling risk allocation decision-making process in public–private partnership (PPP) …