@ARTICLE{Vakhshouri_B._Predykcja_2015,
 author={Vakhshouri, B. and Nejadi, S.},
 number={No 2},
 journal={Archives of Civil Engineering},
 pages={53-72},
 howpublished={online},
 year={2015},
 publisher={WARSAW UNIVERSITY OF TECHNOLOGY FACULTY OF CIVIL ENGINEERING and COMMITTEE FOR CIVIL ENGINEERING POLISH ACADEMY OF SCIENCES},
 abstract={Light-weight Self-Compacting Concrete (LWSCC) might be the answer to the increasing construction requirements of slenderer and more heavily reinforced structural elements. However there are limited studies to prove its ability in real construction projects. In conjunction with the traditional methods, artificial intelligent based modeling methods have been applied to simulate the non-linear and complex behavior of concrete in the recent years. Twenty one laboratory experimental investigations on the mechanical properties of LWSCC; published in recent 12 years have been analyzed in this study. The collected information is used to investigate the relationship between compressive strength, elasticity modulus and splitting tensile strength in LWSCC. Analytically proposed model in ANFIS is verified by multi factor linear regression analysis. Comparing the estimated results, ANFIS analysis gives more compatible results and is preferred to estimate the properties of LWSCC.},
 type={Artykuły / Articles},
 title={Predykcja wytrzymałości na ściskanie lekkiego betonu samouszczelniającego wg modelu analitycznego ANFIS},
 title={Predicition of compressive strength in light-weight Self-Compacting Concrete by ANFIS analytical model},
 URL={http://ochroma.man.poznan.pl/Content/84010/mainfile.pdf},
 keywords={ANFIS, analiza regresji, lekki beton samouszczelniający, wytrzymałość na ściskanie, moduł sprężystości, wytrzymałość na rozciąganie, ANFIS, regression analysis, light-weight self-compacting concrete, compressive strength, elasticity modulus, splitting tensile strength},
}