Prediction of compressive strength of concrete

• Main Authors: Varma, M. Satish, Jain, Akshitha, Hemanth, B., Satwik, J., Sai, A. Bhaskar
• Format: Conference Proceeding
• Language: English
• Subjects: Compressive strength; Concrete construction; Concrete properties; Construction; Estimates; Machine learning; Mathematical models; Parameters; Quality control
• ISSN: 0094-243X; 1551-7616
• DOI: 10.1063/5.0115435

An important parameter of a state structure is the concrete's compressive strength. Concrete's compressive strength is an incompatible function with its components. In the initial phases of construction and the quality control of construction, concrete strength estimates are vital. Estimates of concrete strength play an important role in the initial phase of construction and in the control of construction quality. Predicting of concrete strength relating to the problem of obtaining Concrete Pressure Power according to certain parameters. For this we have taken a set of data. This method detects the concrete strength of a given input given as parameters. Concrete is a material used in construction that is highly flexible and contains good pressure, durability and performance. A major problem in construction is to speculate the compressive strength of cement in order to consider the exact amount of other materials to be used. We predict the compression strength of the concrete using the Machine learning method, so that we can quickly determine the results manually without wasting time using data collected in the past. This Model also trains and evaluates the number of people provided with concrete and with a highly efficient machine learning model can predict concrete strength with much greater accuracy than traditional methods