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Cementation of low-level radioactive waste of complex chemistry investigation of the combined action of borate, chloride, sulfate and phosphate on cement hydration using response surface methodology
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Comparison between genetic algorithm and response surface methodology in GMAW welding optimization
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Models relating mixture composition to the density and strength of Foam concrete using response surface methodology
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Kunhanandan Nambiar, E.K. and K. Ramamurthy, 2006. Models relating mixture composition to the density and strength of Foam concrete using response surface methodology. Cem. Concr. Composites, 28: 752-760.
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Modeling the compressive strength of molasses-cement sand system using design of experiments and back propagation neural network
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Mandal, A. and P. Roy, 2006. Modeling the compressive strength of molasses-cement sand system using design of experiments and back propagation neural network. J. Mater. Process. Technol., 80: 167-173.
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Application of response surface methodology in the optimization of cutting conditions for surface roughness
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Determination of effecting dimensional parameters onwarpage of thin shell plastic parts using integrated response surface method and genetic algorithm
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Ozcelik, B. and T. Erzurumlu, 2005. Determination of effecting dimensional parameters onwarpage of thin shell plastic parts using integrated response surface method and genetic algorithm. Int. Commun. Heat Mass Transfer, 32: 1085-1094.
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A genetic algorithm approach for optimization of surface roughness prediction model
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Suresh, P. V.S., P. Venkateswara Rao and S.G. Deshmukh, 2002. A genetic algorithm approach for optimization of surface roughness prediction model. Int. J. Mach. Tools Manuf., 42: 675-680.
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