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On the uncertainty analysis of uplift capacity of suction caissons in clay based on the fuzzy sets theory

机译:基于模糊集理论的黏土沉箱提升能力不确定性分析

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Uncertainties in the input parameters of predictive models for uplift capacity of suction caisson lead to uncertain performance. To account for the influence of such uncertainties on the suction caisson stability, a fuzzy model is employed. The input uncertainties are introduced to the predictive formulas by triangular membership functions. To obtain the extreme values of the uplift capacity, optimization problems with many objectives are solved by the coupling of genetic algorithm (GA) with the uplift capacity estimation models. The relationships derived by different methods for the prediction of the uplift capacity, are analyzed by the fuzzy approach using a compiled database. Through the membership functions of several statistical measures, it is inferred that small input uncertainties can significantly affect the responses. Also, the recently proposed "M5-GP" - based prediction models are found to be vulnerable to input uncertainties, hence, a new revision called "Improved M5GP" model is developed. Finally, it is shown that the presented model is the best among various models regarding the reliability as well as the accuracy.
机译:吸水沉箱提升能力的预测模型输入参数的不确定性导致性能不确定。为了解决此类不确定性对沉箱稳定性的影响,采用了模糊模型。通过三角隶属度函数将输入不确定性引入预测公式。为了获得提升能力的极值,通过将遗传算法(GA)与提升能力估算模型相结合,解决了许多目标的优化问题。使用已编译的数据库,通过模糊方法分析了通过不同方法预测提升能力的关系。通过几种统计度量的隶属函数,可以推断出小的输入不确定性会显着影响响应。而且,发现最近提出的基于“ M5-GP”的预测模型容易受到输入不确定性的影响,因此,开发了称为“改进的M5GP”模型的新修订版。最后,从可靠性和准确性的角度出发,表明所提出的模型是各种模型中最好的。

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