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Results 1-8 of 8 (Search time: 0.002 seconds).
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Issue Date
Title
Author(s)
2023
Prediction of masonry prism strength using machine learning technique: Effect of dimension and strength parameters
Sathiparan, N.
;
Pratheeba, J.
2023
Soft computing techniques to predict the compressive strength of groundnut shell ash-blended concrete
Sathiparan, N.
;
Pratheeba, J.
2023
Surface response regression and machine learning techniques to predict the characteristics of pervious concrete using non-destructive measurement: Ultrasonic pulse velocity and electrical resistivity
Sathiparan, N.
;
Pratheeba, J.
;
Daniel Niruban, S.
2023
Predicting compressive strength of cementstabilized earth blocks using machine learning models incorporating cement content, ultrasonic pulse velocity, and electrical resistivity
Sathiparan, N.
;
Pratheeba, J.
2023
Effect 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 techniques
Sathiparan, N.
;
Pratheeba, J.
;
Daniel Niruban, S.
2023
Soft computing techniques to predict the electrical resistivity of pervious concrete
Daniel Niruban, S.
;
Pratheeba, J.
;
Sathiparan, N.
2023
Prediction of compressive strength of fly ash blended pervious concrete: a machine learning approach
Sathiparan, N.
;
Pratheeba, J.
;
Daniel Niruban, S.
2023
Use of soft computing approaches for the prediction of compressive strength in concrete blends with eggshell powder
Sathiparan, N.
;
Pratheeba, J.
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Author
4
Daniel Niruban, S.
Subject
4
Compressive strength
4
Pervious concrete
2
Compaction energy
2
Electrical resistivity
2
SHAP
2
SHAP analysis
2
UPV
1
ANN
1
Concrete
1
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Date issued
8
2023
Has File(s)
8
true