COI code: ICCAU01_2984
Paper Language: English
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Authors artificial intelligence for modeling of civil engineering nonlinear systems:compressive strength and slump flow of HPCpooria dehghan - Department of Geology, Ferdowsi University of Mashhad, Mashhad, Iran
amir h.alavi - Department of Civil and Environmental Engineering, Engineering Building, Michigan State University, East Lansing , USA
amir h.gandomi - Department of Civil Engineering, The University of Akron, Akron, OH 44325, USA.
mohammad ghafoori - Department of Geology, Ferdowsi University of Mashhad, Mashhad, Iran
Abstract:The main aim of this study is to illustrate the capabilities of a new branch of artificial intelligence techniques namely, gene expression programming (GEP) for the formulation of complex civil engineering problems. For this purpose, the GEP method is utilized to derive new design equations for compressive strength and slump flow of high performance concrete (HPC) mixes. GEP is found to be an effective method for deriving simplified and precise formulations for the compressive strength and slump flow of HPC. Based on the results, GEP can be considered as a valuable tool for capturing nonlinear interactions between various parameters of civil engineering systems
Keywords:Artificial intelligence, Gene expression programming, High performance concrete, Prediction
COI code: ICCAU01_2984
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dehghan, pooria; amir h.alavi; amir h.gandomi & mohammad ghafoori, 2013, artificial intelligence for modeling of civil engineering nonlinear systems:compressive strength and slump flow of HPC, International conference on civil engineering, architecture and Urban Sustainable Development, تبريز, دانشگاه آزاد اسلامي واحد تبريز, https://www.civilica.com/Paper-ICCAU01-ICCAU01_2984.htmlInside the text, wherever referred to or an achievement of this article is mentioned, after mentioning the article, inside the parental, the following specifications are written.
First Time: (dehghan, pooria; amir h.alavi; amir h.gandomi & mohammad ghafoori, 2013)
Second and more: (dehghan; h.alavi; h.gandomi & ghafoori, 2013)
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Type: state university
Paper No.: 25154
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