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Results 11421-11430 of 11801 (Search time: 0.011 seconds).
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Issue DateTitleAuthor(s)
2024Prediction of moisture content of cementstabilized earth blocks using soil characteristics, cement content, and ultrasonic pulse velocitySathiparan, N.; Tharuka, R.A.N.S.; Jeyananthan, P.
2025Comparative analysis of machine learning models and standard codes for predicting compressive strength in hollow block masonrySathiparan, N.; Jeyananthan, P.
2023Predicting compressive strength of cementstabilized earth blocks using machine learning models incorporating cement content, ultrasonic pulse velocity, and electrical resistivitySathiparan, N.; Jeyananthan, P.
2025Mathematical Model and Machine Learning Techniques to Predict the Compressive Strength of Groundnut Shell Ash Blended SandcreteSathiparan, N.; Jeyananthan, P.
2025Statistical investigation of aggregate size and shape impact on porosity and compressive strength of pervious concreteSajeevan, M.; Ahilash, N.; Shobijan, J.; Pravinjan, V.; Virupashan, K.; Sathiparan, N.; Subramaniam, D.N.
2023Compression and Bond Properties of Fired Clay Brick Masonry with Cocopeat Blended Binding MortarMuralitharan, M.; Sathiparan, N.
2023Statistical Assessment of Different Aggregate Shape FactorsWijekoon, S.H.B.; Subramaniam, D.N.; Sathiparan, N.
2024Silica fume as a supplementary cementitious material in pervious concrete: prediction of compressive strength through a machine learning approachSathiparan, N.; Jeyananthan, P.; Subramaniam, D.N.
2024Quantifying the impact of chemical composition on pervious concrete strength: a comparative analysis using full quadratic model and artificial neural networkSathiparan, N.; Jeyananthan, P.; Subramaniam, D.N.
2025Response surface regression and machine learning models to predict the porosity and compressive strength of pervious concrete based on mix design parametersSathiparan, N.; Wijekoon, S.H.; Ravi, R.; Jeyananthan, P.; Subramaniam, D.N.

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