I-Cheng Yeh, "Modeling of strength of high performance concrete using artificial neural networks," Cement and Concrete Research, Vol. I-Cheng Yeh and the following published paper: NOTE: Reuse of this database is unlimited with retention of copyright notice for Prof. Yeh, I-Cheng, "Analysis of strength of concrete using design of experiments and neural networks," Journal of Materials in Civil Engineering, ASCE, Vol.18, No.4, pp.597-604 (2006). I-Cheng Yeh, "A mix Proportioning Methodology for Fly Ash and Slag Concrete Using Artificial Neural Networks," Chung Hua Journal of Science and Engineering, Vol. I-Cheng Yeh, "Prediction of Strength of Fly Ash and Slag Concrete By The Use of Artificial Neural Networks," Journal of the Chinese Institute of Civil and Hydraulic Engineering, Vol. of Computing in Civil Engineering, ASCE, Vol. I-Cheng Yeh, "Design of High Performance Concrete Mixture Using Neural Networks," J. of Materials in Civil Engineering, ASCE, Vol. I-Cheng Yeh, "Modeling Concrete Strength with Augment-Neuron Networks," J. The Department of Civil and Environmental Engineering focuses its graduate study and research program on three areas: Structural Engineering, including engineering mechanics, advanced composites, structural dynamics, earthquake engineering, and reliability and risk assessment Transportation Systems Engineering, including traffic operations and. Superplasticizer (component 5) - quantitative - kg in a m3 mixture - Input VariableĬoarse Aggregate (component 6) - quantitative - kg in a m3 mixture - Input Variableįine Aggregate (component 7) - quantitative - kg in a m3 mixture - Input VariableĪge - quantitative - Day (1~365) - Input VariableĬoncrete compressive strength - quantitative - MPa - Output Variableġ. Civil Engineering addresses the technology of constructed environments and, as such, embraces a wide range of intellectual endeavors. Water (component 4) - quantitative - kg in a m3 mixture - Input Variable Name - Data Type - Measurement - DescriptionĬement (component 1) - quantitative - kg in a m3 mixture - Input Variableīlast Furnace Slag (component 2) - quantitative - kg in a m3 mixture - Input Variableįly Ash (component 3) - quantitative - kg in a m3 mixture - Input Variable The order of this listing corresponds to the order of numerals along the rows of the database. The concrete compressive strength is the regression problem. Given are the variable name, variable type, the measurement unit and a brief description. The concrete compressive strength is a highly nonlinear function of age and ingredients.Īttribute breakdownĘ quantitative input variables, and 1 quantitative output variable Click here to try out the new site.ĭownload: Data Folder, Data Set DescriptionĪbstract: Concrete is the most important material in civil engineering. Check out the beta version of the new UCI Machine Learning Repository we are currently testing! Contact us if you have any issues, questions, or concerns.
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