Concrete compressive strength prediction modeling utilizing deep learning long short-term memory algorithm for a sustainable environment - Latif, Sarmad Dashti (Environmental science and pollution research international, 2021)
Keywords: Algorithms; Aquatic Pollution; Atmospheric Protection/Air Quality Control/Air Pollution; Blast furnace practice; Blast furnace slags; cement; compression strength; Compressive Strength; Concrete; Concrete properties; Construction Materials; data collection; Deep Learning; Design parameters; Earth and Environmental Science; Ecotoxicology; Environment; Environmental Chemistry; Environmental Health; Environmental impact; Environmental science; environmental sustainability; Fly ash; furnaces; humidity; Learning algorithms; Long short-term memory; Machine learning; Mathematical models; neural networks; Neural Networks, Computer; prediction; Prediction models; Research Article; Root-mean-square errors; Severe weather; Slag; slags; Statistical analysis; Superplasticizers; Support vector machines; Waste Water Technology; Water Management; Water Pollution Control; Weather; Deep learning; Concrete strength prediction; Support vector machine (SVM); Long short-term memory (LSTM); High-performance concrete (HPC)