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@article{151013,
        author = {Reba Iram and P. O. Modani},
        title = {Literature Review on Prediction of Compressive Strength of Concrete Using Artificial Neural Network},
        journal = {International Journal of Innovative Research in Technology},
        year = {},
        volume = {7},
        number = {11},
        pages = {376-380},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=151013},
        abstract = {The compressive strength of concrete is the mostly used criterion in producing concrete. Compressive strength of concrete is determined by destructive testing of control specimens in a Compression Testing Machine (CTM) but testing for these specimens is a complicated and tedious task. Also, the test specimens are not an exact representation of in-situ concrete. As the test is usually performed after 28 days of curing of concrete at the construction site, it is too late to make improvement if the results does not satisfy the required strength. Therefore, it is highly desirable to predict the strength of concrete before the placement. Application of Artificial Neural Network technique to predict the strength of concrete based on different parameters and characteristics of concrete is reliable and efficient. ANN makes the task easy and provides in-situ strength of concrete in very less time with reasonable accuracy.},
        keywords = {Artificial Neural Network (ANN), Compressive Strength, Concrete, Prediction},
        month = {},
        }