A comparison of novel hybrid ensemble learners to predict the compressive strength of green engineering materials: a case of concrete composed of rice husk ash
Ali Reza Ghanizadeh, Amir Tavana Amlashi, Samer Dessouky, Seyed Abolfazl Ebrahimi
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Abstract
The use of ensemble learning (EL) has grown due to its ability to enhance precision in predictions compared to typical machine learning (ML) algorithms. EL-based approaches are expected to be more ...
期刊介绍：
The European Research Area has now become a reality. The prime objective of the EJECE is to fully document advances in International scientific and technical research in the fields of sustainable construction and soil engineering. In particular regard to the latter, the environmental preservation of natural media (soils and rocks) and the mitigation of soil-related risks are now not only major societal challenges, but they are also the source of scientific and technical developments that could be extremely beneficial.
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