首页|Findings from Muzaffarpur Institute of Technology (MIT Muzaffarpur) Provides New Data about Machine Learning (Prediction of Compressive Strength of High-volume Fly Ash Self-compacting Concrete With Silica Fume Using Machine Learning Techniq ues)
Findings from Muzaffarpur Institute of Technology (MIT Muzaffarpur) Provides New Data about Machine Learning (Prediction of Compressive Strength of High-volume Fly Ash Self-compacting Concrete With Silica Fume Using Machine Learning Techniq ues)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News – Data detailed on Machine Learning have been presented. According to news reportingoriginating in Muzaffarpur, India, by NewsRx journalists, research stated, “The quality and compositionof the comp onents in Self-Compacting Concrete (SCC) determine its compressive strength; how ever,determining these complex relationships through traditional statistical me thods is difficult. This study usesfive state-of-the-art machine learning techn iques, namely, Random Forest (RF), Adaboost, ConvolutionalNeural Network (CNN), K-Nearest Neighbor (KNN), and Bidirectional Long Short-Term Memory (BILSTM),t o simulate the strength properties of high-volume fly ash self-compacting concre te (HVFA-SCC)with silica fume.”
MuzaffarpurIndiaAsiaCyborgsEmerg ing TechnologiesMachine LearningMuzaffarpur Institute of Technology (MIT Muz affarpur)
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