Yan Shi

发表

Mixed kernel function support vector regression for global sensitivity analysis

Zhenzhou Lu, Kai Cheng, Zhenzhou Lu, 2017 .

AN OPTIMAL MULTIVARIABLE GREY MODEL FOR LOGISTICS DEMAND FORECAST

Fachao Li, Hongqi Hui, Yan Shi, 2013 .

Sensitivity analysis method for model with correlated inputs and multivariate output and its application to aircraft structure

Zhenzhou Lu, Liyang Xu, Yan Shi, 2019, Computer Methods in Applied Mechanics and Engineering.

A vine copula–based method for analyzing the moment-independent importance measure of the multivariate output

Zhenzhou Lu, Kai Cheng, Yan Shi, 2018, Proceedings of the Institution of Mechanical Engineers, Part O: Journal of Risk and Reliability.

RESEARCH ON THE THEORY AND METHOD OF ROUGH PROGRAMMING BASED ON SYNTHESIS EFFECT

Fachao Li, Chenxia Jin, Yan Shi, 2013 .

Temporal and spatial multi-parameter dynamic reliability and global reliability sensitivity analysis based on the extreme value moments

Zhenzhou Lu, Kai Cheng, Yan Shi, 2017, Structural and Multidisciplinary Optimization.

Novel fuzzy possibilistic safety degree measure model

Zhenzhou Lu, Yan Shi, 2019, Structural and Multidisciplinary Optimization.

Time-dependent safety and sensitivity analysis for structure involving both random and fuzzy inputs

Zhenzhou Lu, Yan Shi, Yicheng Zhou, 2018, Structural and Multidisciplinary Optimization.

Novel decoupling method for time-dependent reliability-based design optimization

Zhenzhou Lu, Liyang Xu, Yan Shi, 2019, Structural and Multidisciplinary Optimization.

Constitutive model for high temperature deformation of titanium alloys using internal state variables

Jiao Luo, Miaoquan Li, Xiaolin Li, 2010 .

The Bayesian quantile regression method in accelerated life tests

Zhenzhou Lu, Kai Cheng, Zhenzhou Lu, 2016 .

Global sensitivity analysis for fuzzy inputs based on the decomposition of fuzzy output entropy

Zhenzhou Lu, Zhenzhou Lu, Yan Shi, 2017 .

Advanced time-dependent reliability analysis based on adaptive sampling region with Kriging model

Yan Shi, Zhenzhou Lu, Ruyang He, 2020 .

An expanded sparse Bayesian learning method for polynomial chaos expansion

Yan Shi, Zhenzhou Lu, Kai Cheng, 2019, Mechanical Systems and Signal Processing.

Temporal and spatial multi-parameter dynamic reliability and global reliability sensitivity analysis based on the extreme value moments

Zhenzhou Lu, Kai Cheng, Zhenzhou Lu, 2017 .

Sensitivity analysis of correlated outputs and its application to a dynamic model

Yan Shi, Zhenzhou Lu, Luyi Li, 2018, Environ. Model. Softw..

An Analytic Model for Skin Modulus Measurement Via Conformal Piezoelectric Systems

John A. Rogers, Canan Dagdeviren, Yonggang Huang, 2015 .

Novel fuzzy possibilistic safety degree measure model

Yan Shi, Zhenzhou Lu, Zhenzhou Lu, 2020, Structural and Multidisciplinary Optimization.

A novel time-dependent system constraint boundary sampling technique for solving time-dependent reliability-based design optimization problems

Enrico Zio, Zhenzhou Lu, Yan Shi, 2020 .

Advanced solution strategies for time-dependent reliability based design optimization

Yan Shi, Liyang Xu, Zhenzhou Lu, 2020, Computer Methods in Applied Mechanics and Engineering.

Bayesian optimum accelerated life test plans based on quantile regression

Yan Shi, Zhenzhou Lu, Yicheng Zhou, 2020, Commun. Stat. Simul. Comput..

Time-dependent reliability-based design optimization with probabilistic and interval uncertainties

Yan Shi, Zhenzhou Lu, Zhiliang Huang, 2020 .

FUZZY SYNTHETIC EVALUATION MODEL BASED ON THE KNOWLEDGE SYSTEM

Fachao Li, Chenxia Jin, Yan Shi, 2013 .

A generalized equilibrium value-based approach for solving fuzzy transportation problems with triangular fuzzy numbers

Yan Shi, Chenxia Jin, Fachao Li, 2014, 2014 Joint 7th International Conference on Soft Computing and Intelligent Systems (SCIS) and 15th International Symposium on Advanced Intelligent Systems (ISIS).

Time-dependent reliability-based design optimization considering aleatory and epistemic uncertainties

Enrico Zio, Zhenzhou Lu, Yan Shi, 2020, Structural and Multidisciplinary Optimization.

Dynamic reliability analysis model for structure with both random and interval uncertainties

Yan Shi, Zhenzhou Lu, Yan Shi, 2018, International Journal of Mechanics and Materials in Design.

Dynamic reliability analysis model for structure with both random and interval uncertainties

Yan Shi, Z. Lu, 2018, International Journal of Mechanics and Materials in Design.

Global Sensitivity Analysis of the Failure Probability Upper Bound to Random and Fuzzy Inputs

Yan Shi, Zhenzhou Lu, Lufeng Zhao, 2018, Int. J. Fuzzy Syst..

Global Sensitivity Analysis of the Failure Probability Upper Bound to Random and Fuzzy Inputs

Yan Shi, Lufeng Zhao, Zhenzhou Lu, 2018, International Journal of Fuzzy Systems.

Global sensitivity analysis using support vector regression

Zhenzhou Lu, Kai Cheng, Kai Cheng, 2017 .

STUDY ON QUASI-LINEAR REGRESSION METHODS

Fachao Li, Chenxia Jin, Yan Shi, 2012 .

A novel learning function based on Kriging for reliability analysis

Yan Shi, Zhenzhou Lu, Siyu Chen, 2020, Reliab. Eng. Syst. Saf..

A reliability analysis method based on analytical expressions of the first four moments of the surrogate model of the performance function

Yan Shi, Zhenzhou Lu, Liyang Xu, 2018, Mechanical Systems and Signal Processing.

Time-dependent safety and sensitivity analysis for structure involving both random and fuzzy inputs

Yan Shi, Zhenzhou Lu, Yicheng Zhou, 2018, Structural and Multidisciplinary Optimization.

Reliability analysis for structures with multiple temporal and spatial parameters based on the effective first-crossing point

Kaichao Zhang, Zhenzhou Lu, Yuhao Wei, 2017 .

Variational Bayesian inference-based polynomial chaos expansion: Application to time-variantreliability analysis

Changcong Zhou, Wanying Yun, Yan Shi, 2021, Proceedings of the Institution of Mechanical Engineers, Part O: Journal of Risk and Reliability.

An adaptive multiple-Kriging-surrogate method for time-dependent reliability analysis

Yan Shi, Zhenzhou Lu, Liyang Xu, 2019, Applied Mathematical Modelling.