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首页> 外文期刊>International journal of food properties >Dynamic Mechanical Spectra of Selected Turkish Honeys: Construction of Predictive Models for Complex Viscosity Using Two Different Nonlinear Modeling Techniques
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Dynamic Mechanical Spectra of Selected Turkish Honeys: Construction of Predictive Models for Complex Viscosity Using Two Different Nonlinear Modeling Techniques

机译:精选土耳其蜂蜜的动态力学谱:使用两种不同的非线性建模技术构建复杂粘度的预测模型

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Dynamic oscillatory shear rheological characteristics of honey samples from different floral sources were evaluated using frequency sweep test and stress sweep test at three different temperatures (10, 15, and 20°C). All honey samples showed liquid-like behavior because the loss modulus was significantly greater than the elastic modulus. Pine honey showed the highest complex viscosity (86.33 Pa s at 10°C), while the lowest complex viscosity was observed in citrus honey (22.15 Pa s) at the same temperature. Temperature dependency of complex viscosity of honey samples was modeled by Arrhenius model and activation energy values of honeys ranged from 83.13 to 97.46 kJ/mol. An efficient predictive model for complex viscosity values of honeys was constructed using adaptive neuro fuzzy inference system that showed satisfactory prediction performance with high coefficient of determination (0.995) and low root mean square error (0.04) in the validation period compared to artificial neural networks.
机译:使用频率扫描测试和应力扫描测试在三种不同温度(10、15和20°C)下评估了来自不同花卉来源的蜂蜜样品的动态振荡剪切流变特性。所有的蜂蜜样品都表现出类似液体的行为,因为其损耗模量明显大于弹性模量。松蜂蜜显示出最高的复数粘度(在10°C下为86.33 Pa s),而柑橘蜂蜜在相同温度下观察到的最低复数粘度(22.15 Pa s)。用Arrhenius模型模拟了蜂蜜样品复粘度的温度依赖性,蜂蜜的活化能值在83.13至97.46 kJ / mol之间。使用自适应神经模糊推理系统构建了一个有效的蜂蜜复杂粘度值预测模型,与人工神经网络相比,该模型在验证期内显示出令人满意的预测性能,具有较高的测定系数(0.995)和较低的均方根误差(0.04)。

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