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Issue DateTitleAuthor(s)
2023Prediction of masonry prism strength using machine learning technique: Effect of dimension and strength parametersSathiparan, N.; Pratheeba, J.
2023Soft computing techniques to predict the compressive strength of groundnut shell ash-blended concreteSathiparan, N.; Pratheeba, J.
2023Surface response regression and machine learning techniques to predict the characteristics of pervious concrete using non-destructive measurement: Ultrasonic pulse velocity and electrical resistivitySathiparan, N.; Pratheeba, J.; Daniel Niruban, S.
2023Predicting compressive strength of cementstabilized earth blocks using machine learning models incorporating cement content, ultrasonic pulse velocity, and electrical resistivitySathiparan, N.; Pratheeba, J.
2022Tracking Everyone and Everything in Smart Cities with an ANN Driven Smart AntennaHerman, K.; Hoole, P.R.P.; Pirapaharan, K.; Hoole, S.R.H.
2023Effect of aggregate size, aggregate to cement ratio and compaction energy on ultrasonic pulse velocity of pervious concrete: prediction by an analytical model and machine learning techniquesSathiparan, N.; Pratheeba, J.; Daniel Niruban, S.
2023Soft computing techniques to predict the electrical resistivity of pervious concreteDaniel Niruban, S.; Pratheeba, J.; Sathiparan, N.
2023Prediction of compressive strength of fly ash blended pervious concrete: a machine learning approachSathiparan, N.; Pratheeba, J.; Daniel Niruban, S.
2023Use of soft computing approaches for the prediction of compressive strength in concrete blends with eggshell powderSathiparan, N.; Pratheeba, J.