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RBF神经网络 2

围岩变形 2

神经网络 2

AR模型 1

BP神经网络 1

RBF网络 1

侵彻混凝土深度 1

变形预测 1

地下水 1

径向基函数(RBF) 1

径向基函数(RBF)神经网络 1

振动信号 1

模式识别 1

水文地质参数 1

滚动轴承 1

群智能；苍狼优化算法；优化；RBF（radial basis function）网络 1

连拱隧洞 1

量纲分析 1

隧洞施工 1

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基于RBF神经网络的隧洞围岩变形预测方法

张俊艳,冯守中,刘东海

《中国工程科学》 2005年第7卷第10期页码 87-90

摘要：提出的基于RBF神经网络的隧道围岩变形预测方法，不仅能很好地描述复杂的围岩变形时程曲线，而且比BP神经网络具有更快的收敛速度和更好的全局搜索能力。实例研究验证了该方法的有效性与可行性。

关键词： RBF神经网络隧洞施工围岩变形预测

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基于RBF神经网络算法的连拱隧道围岩变形预测方法研究

肖智旺,钟登华

《中国工程科学》 2008年第10卷第7期页码 77-81

摘要：

利用径向基函数前馈式神经网络的特性，构建了连拱隧洞围岩变形的预测模型，并利用Matlab工具对模型进行求解。最后的工程实例对文章的方法进行了检验，其结果表明，此方法具有求解速度快，结果更为优化、预测效果更好等优点。

关键词：连拱隧洞围岩变形变形预测径向基函数(RBF) 神经网络

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基于RBF神经网络的水文地质参数识别

张俊艳,魏连伟,韩文秀,邵景力,崔亚丽,张建立

《中国工程科学》 2004年第6卷第8期页码 74-78

摘要：针对传统水文地质参数识别方法的局限性，提出了水文地质参数识别的径向基函数(RBF )神经网络方法，并通过算例验证了它的可行性与有效性，实现了水文地质参数的自动识别，提高了计算效率，比BP神经网络具有更好的参数识别效果

关键词：地下水水文地质参数径向基函数(RBF)神经网络 BP神经网络

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Reliability-based design optimization of offshore wind turbine support structures using RBF surrogate

《结构与土木工程前沿（英文）》页码 1086-1099 doi: 10.1007/s11709-023-0976-8

摘要： Reliability-based design optimization of offshore wind turbine support structures using RBF surrogate model

关键词： RBF surrogate model turbine support structures

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Multiscale RBF-based central high resolution schemes for simulation of generalized thermoelasticity problems

Hassan YOUSEFI, Alireza TAGHAVI KANI, Iradj MAHMOUDZADEH KANI

《结构与土木工程前沿（英文）》 2019年第13卷第2期页码 429-455 doi: 10.1007/s11709-018-0483-5

摘要： In this study, average-interpolating radial basis functions (RBFs) are successfully integrated with central high-resolution schemes to achieve a higher-order central method. This proposed method is used for simulation of generalized coupled thermoelasticity problems including shock (singular) waves in their solutions. The thermoelasticity problems include the LS (systems with one relaxation parameter) and GN (systems without energy dissipation) theories with constant and variable coefficients. In the central high resolution formulation, RBFs lead to a reconstruction with the optimum recovery with minimized roughness on each cell: this is essential for oscillation-free reconstructions. To guarantee monotonic reconstructions at cell-edges, the nonlinear scaling limiters are used. Such reconstructions, finally, lead to the total variation bounded (TVB) feature. As RBFs work satisfactory on non-uniform cells/grids, the proposed central scheme can handle adapted cells/grids. To have cost effective and accurate simulations, the multiresolution–based grid adaptation approach is then integrated with the RBF-based central scheme. Effects of condition numbers of RBFs, computational complexity and cost of the proposed scheme are studied. Finally, different 1-D coupled thermoelasticity benchmarks are presented. There, performance of the adaptive RBF-based formulation is compared with that of the adaptive Kurganov-Tadmor (KT) second-order central high-resolution scheme with the total variation diminishing (TVD) property.

关键词： central high resolution schemes RBFs higher order accuracy generalized thermoelasticity multiresolution-based adaptation