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- W4386988436 abstract "The object of the present research paper is to develop Artificial Neural Network Simulation and by using five Ï-term from four independent pi terms. (Aspect ratio, aggregate-cement ratio, water-cement ratio, percentage of fibre and control strength)) for prediction of SFRC Split Tensile strength. The output of this network can be evaluated by comparing it with experimental strength and the predicted ANN simulation strength. The study becomes more fruitful when most influencing Ï-term is calculated for the prediction of SFRC strength. The beauty of the models is that we can predict compressive strength, flexural strength and split tensile strength by using same model." @default.
- W4386988436 created "2023-09-24" @default.
- W4386988436 date "2023-09-01" @default.
- W4386988436 modified "2023-09-29" @default.
- W4386988436 title "PREDICTION OF SFRC SPLIT TENSILE STRENGTH BY ARTIFICIAL NEURAL NETWORK (ANN) WITH CONTROL STRENGTH AND 4 INDEPENDENT PIE TERMS" @default.
- W4386988436 doi "https://doi.org/10.48047/ecb/2023.12.si10.0057" @default.
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