Automatic lung cancer detection from CT image using improved deep neural network and ensemble classifier

PM Shakeel, MA Burhanuddin, MI Desa - Neural Computing and …, 2022 - Springer
The development of the computer-aided detection system placed an important role in the
clinical analysis for making the decision about the human disease. Among the various …

Estimation at completion in civil engineering projects: review of regression and soft computing models

AM Araba, ZA Memon… - Knowledge …, 2021 - … journals.publicknowledgeproject.org
Construction projects are usually associated with several challenges owing to the varying
process during the project lifetime. Hence, the final cost of any civil engineering project is …

The expectations of project managers from artificial intelligence: A Delphi study

V Holzmann, D Zitter… - Project Management …, 2022 - journals.sagepub.com
Artificial intelligence (AI) technologies are rapidly develo** these days and are expected
to impact the field of project management on multiple levels; however, there remains a high …

Application of predictive analytics in built environment research: A comprehensive bibliometric study to explore knowledge domains and future research agenda

A Halder, S Batra - Archives of Computational Methods in Engineering, 2023 - Springer
The built environment (BE) sector has seen a significant digital transformation in the past few
decades. While predictive analytics (PA) plays a critical role in such a transition. Applications …

Estimate-at-completion (EAC) prediction using Archimedes optimization with adaptive fuzzy and neural networks

AA Mhady, C Budayan, AP Gurgun - Automation in Construction, 2024 - Elsevier
Construction companies estimate project costs at the beginning of the project; however,
many factors impact the final project cost. Estimate at Completion (EAC) is a critical …

[HTML][HTML] Unsupervised machine learning for project stakeholder classification: Benefits and limitations

C Mariani, Y Navrotska, M Mancini - Project Leadership and Society, 2023 - Elsevier
The literature has shown that an accurate classification of project stakeholders allows for
more comprehensive planning of their management strategies. The most used classification …

Using machine learning to improve cost and duration prediction accuracy in green building projects

A Darko, I Glushakova, EB Boateng… - Journal of Construction …, 2023 - ascelibrary.org
A major source of risk in green building projects (GBPs) is inaccurate human prediction of
the final project cost and duration, which in turn results in cost and schedule overruns (ie …

Short‐Term Electrical Load Demand Forecasting Based on LSTM and RNN Deep Neural Networks

B Islam, SF Ahmed - Mathematical Problems in Engineering, 2022 - Wiley Online Library
As the development of smart grids is increasing, accurate electric load demand forecasting
is becoming more important for power systems, because it plays a vital role to improve the …

Predictive Hybridization Model integrating Modified Genetic Algorithm (MGA) and C4. 5

JCM Bustillo, RP Medina, AM Sison… - 2022 6th International …, 2022 - ieeexplore.ieee.org
Numerous enhancements of prediction models through hybridization and combining various
machine learning to increase the prediction model's performance are still an ongoing …

Artificial intelligence in construction projects: An explorative study of professionals' expectations

V Holzmann, M Lechiara - European Journal of Business and …, 2022 - ejbmr.org
Artificial intelligence (AI) is a fast-growing innovative technology that will have a huge impact
on projects and project management practices in the forthcoming years. The purpose of this …