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Determination of Compressive Strength of Concrete via Artificial Intelligence
Concrete is the most vital composite construction material in industry of construction due to its properties/benefits like compressive strength, flexural strength, low permeability, resistance to fire and many more. Compressive strength is a standout property of concrete that can be determined by destructive/ non-destructive test. Due to non-linear behavior of concrete, its compressive strength is very difficult to predict in design and construction phase. Hence, available statistical and empirical non-destructive methods/techniques are not sufficient in predicting strength of concrete (compression). In this review paper three Artificial Intelligence (AI) models/methods named as Artificial Neural Network (ANN), Adaptive Neuro-Fuzzy Inference System (ANFIS) and Fuzzy Inference (FIS) were analyzed for determination of strength of concrete (compression).
Determination of Compressive Strength of Concrete via Artificial Intelligence
Concrete is the most vital composite construction material in industry of construction due to its properties/benefits like compressive strength, flexural strength, low permeability, resistance to fire and many more. Compressive strength is a standout property of concrete that can be determined by destructive/ non-destructive test. Due to non-linear behavior of concrete, its compressive strength is very difficult to predict in design and construction phase. Hence, available statistical and empirical non-destructive methods/techniques are not sufficient in predicting strength of concrete (compression). In this review paper three Artificial Intelligence (AI) models/methods named as Artificial Neural Network (ANN), Adaptive Neuro-Fuzzy Inference System (ANFIS) and Fuzzy Inference (FIS) were analyzed for determination of strength of concrete (compression).
Determination of Compressive Strength of Concrete via Artificial Intelligence
Hussain Mehdi (Autor:in) / Muhammad Usama Salim (Autor:in) / Muhammad Salman Ali (Autor:in)
31.08.2020
oai:zenodo.org:4008873
Journal of Structural Engineering, its Applications and Analysis 3(2) 1-10
Aufsatz (Zeitschrift)
Elektronische Ressource
Englisch
DDC:
690
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