Deep learning and boosted trees for injuries prediction in power infrastructure projects

Oyedele, Ahmed; Ajayi, Anuoluwapo; Oyedele, Lukumon O.; Delgado, Juan Manuel Davila; Akanbi, Lukman; Akinade, Olugbenga; Owolabi, Hakeem; Bilal, Muhammad

doi:10.1016/j.asoc.2021.107587

All Outputs (3)

Rainfall Prediction: A Comparative Analysis of Modern Machine Learning Algorithms for Time-Series Forecasting (2021)
Journal Article

Rainfall forecasting has gained utmost research relevance in recent times due to its complexities and persistent applications such as flood forecasting and monitoring of pollutant concentration levels, among others. Existing models use complex statis... Read More about Rainfall Prediction: A Comparative Analysis of Modern Machine Learning Algorithms for Time-Series Forecasting.

Artificial intelligence in the construction industry: A review of present status, opportunities and future challenges (2021)
Journal Article

The growth of the construction industry is severely limited by the myriad complex challenges it faces such as cost and time overruns, health and safety, productivity and labour shortages. Also, construction industry is one the least digitized industr... Read More about Artificial intelligence in the construction industry: A review of present status, opportunities and future challenges.

Deep learning and boosted trees for injuries prediction in power infrastructure projects (2021)
Journal Article

Electrical injury impacts are substantial and massive. Investments in electricity will continue to increase, leading to construction project complexities, which undoubtedly contribute to injuries and associated effects. Machine learning (ML) algorith... Read More about Deep learning and boosted trees for injuries prediction in power infrastructure projects.