..., their adaptability is constrained by contextual barriers and limited technological integration. Although numerous emerging technologies are available, the integration of machine learning ( ML ) into LCMMs remains largely unexplored. Thus, this study aims to investigate how ML can be fused with LCMMs to improve...

... 08 2023 © Emerald Publishing Limited 2023 Emerald Publishing Limited Licensed re-use rights only Air pollution prediction Big data analytics Ensemble of ensembles IoT Machine learning Air pollution, which includes ozone and outdoor and indoor particulate matter...

.../approach This paper proposes a hybrid model by combining machine learning (ML) techniques with ANN to accurately predict the cost of pile foundations. The parameters contributing toward the cost of pile foundations were collected from five different projects in India. Out of 180 collected data entries...

...Christian Nnaemeka Egwim; Hafiz Alaka; Oluwapelumi Oluwaseun Egunjobi; Alvaro Gomes; Iosif Mporas Purpose This study aims to compare and evaluate the application of commonly used machine learning (ML) algorithms used to develop models for assessing energy efficiency of buildings. Design...

.... This paper aims to investigate the effects traffic data set have on the performance of machine learning (ML) predictive models in AQ prediction. Design/methodology/approach To achieve this, the authors have set up an experiment with the control data set having only the AQ data set and meteorological (Met...

... of this study is the analysis of the neural network's input parameters, which provides insight into the level to which each parameter influences the DC’s energy demand profile. Machine learning Data centre Energy demand prediction Tunicate swarm algorithm The rest of the work presented...

... interviews with industry experts. Findings The enhanced framework has identified that BIM technology would bring the benefit of providing the initial digital data source, from which machine learning and data analytics would then extract the relevant data needed to measure accurately the criteria during...