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Reliability analysis of settlement of pile group

机译:桩群沉降可靠性分析

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Considering the highly variable nature of soil, reliability analysis of pile foundation is being explored in the modern scientific era. The paper investigates the application of relevance vector machines (RVM), generalized regression neural network (GRNN), genetic programming (GP) and adaptive-network-based fuzzy inference (ANFIS) in reliability analysis of settlement of pile group. The simulation is checked using Monte Carlo simulation (M-C). The performance of models is ascertained using various performance parameters and Taylor diagrams. The normality and homogeneity in performance of the models is tested by carrying out Anderson-Darling (AD) test and Mann-Whitney U (M-W) test, respectively. The paper concludes that the performance of RVM, GP and ANFIS were excellent while that of GRNN was poor.
机译:考虑到桩基的高度可变性,在现代科学时代探讨了桩基的可靠性分析。本文研究了相关矢量机(RVM),广义回归神经网络(GRNN),基因编程(GP)和基于自适应网络的模糊推理(ANFIS)在桩基沉降的可靠性分析中的应用。使用Monte Carlo仿真(M-C)检查模拟。使用各种性能参数和泰勒图来确定模型的性能。通过分别进行Anderson-Darling(AD)测试和Mann-Whitney U(M-W)测试来测试模型性能的正常性和均匀性。本文得出结论,RVM,GP和ANFIS的表现优异,而GRNN的性能很差。

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