Ranking of the most influential parameters for compressive strength of no-slump concrete prediction by neuro-fuzzy logic (Retracted Article)
Concrete with low or zero slump is known as no-slump concrete. The main purpose of the no-slump concrete is prefabrication. Determination of compressive strength of the no-clump concrete could be difficult task because of many input variables. These variables represent constituents of the no-slump c...
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| Veröffentlicht in: | Structural concrete : journal of the FIB 2021-04, Vol.22 (2) |
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| container_title | Structural concrete : journal of the FIB |
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| creator | Jovic, Srdjan Babic, Lidija Miskovic, Aleksandar Cirkovic, Bogdan Camagic, Ivica |
| description | Concrete with low or zero slump is known as no-slump concrete. The main purpose of the no-slump concrete is prefabrication. Determination of compressive strength of the no-clump concrete could be difficult task because of many input variables. These variables represent constituents of the no-slump concrete, mixture proportion, complication etc. The no-slump concrete is very sensitive according to the inputs variation and therefore estimation of the compressive strength as the main output factor could be challenging task. Therefore in this study the main aim was to determine influence of the input variables on the compressive strength of the no-slump concrete. The ranking procedure will be done based on regression models. The regression models will be created by adaptive neuro-fuzzy inference system. According to the results silica fume has the strongest influence on the compressive strength prediction of no-slump concrete. The obtained results could be useful in improvement of compressive strength of no-slump concrete. |
| doi_str_mv | 10.1002/suco.201900349 |
| format | Article |
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The main purpose of the no-slump concrete is prefabrication. Determination of compressive strength of the no-clump concrete could be difficult task because of many input variables. These variables represent constituents of the no-slump concrete, mixture proportion, complication etc. The no-slump concrete is very sensitive according to the inputs variation and therefore estimation of the compressive strength as the main output factor could be challenging task. Therefore in this study the main aim was to determine influence of the input variables on the compressive strength of the no-slump concrete. The ranking procedure will be done based on regression models. The regression models will be created by adaptive neuro-fuzzy inference system. According to the results silica fume has the strongest influence on the compressive strength prediction of no-slump concrete. 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| subjects | Construction & Building Technology Engineering Engineering, Civil Science & Technology Technology |
| title | Ranking of the most influential parameters for compressive strength of no-slump concrete prediction by neuro-fuzzy logic (Retracted Article) |
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