000			01738aab a2200229 4500
008			240626b20062006|||br||| |||| 00| 0 eng d
022			_a1598-8198
100			_aTao Ji _9882578
100			_aXu Jian Lin _9882579
245			_aA mortar mix proportion design algorithm based rnon artificial neural networks
300			_a357-373 p.
520			_aThe concepts of four parameters of nominal water-cement ratio, equivalent water-cement ratio, average paste thickness, fly ash-binder ratio were introduced. It was verified that the four parameters and the mix proportion of mortar can be transformed each other. The behaviors (strength, workability, et al.) of mortar primarily determined by the mix proportion of mortar now depend on the four parameters. The prediction models of strength and workability of mortar were built based on artificial neural networks (ANNs). The calculation models of average paste thickness and equivalent water-cement ratio of mortar can be obtained by the reversal deduction of the two prediction models, respectively. A mortar mix proportion design algorithm was proposed. The proposed mortar mix proportion design algorithm is expected to reduce the number of trial and error, save cost, laborers and time.
650			_aMortar Mix Proportion Design _9795379
650			_aArtificial Neural Network (ANN) _9166821
650			_aNominal Water-Cement Ratio _9882580
650			_aEquivalent Water-Cement Ratio _9882581
650			_aAverage Paste Thickness (APT) _9882582
650			_aFly Ash-Binder ratio _9882583
773	0		_dDaejeon, Korea : Techno Press _x15988198 _tComputers and Concrete: An International Journal
856			_uDOI: 10.12989/cac.2006.3.5.357
942			_2ddc _n0 _cART _o14993 _pMr. Muhammad Rafique Al Haj Rajab Ali (Late)
999			_c815312 _d815312