A Lightweight Unified Generative Framework with Prompting for Chinese and English Spoken Language Understanding.
Proceedings of the 28th International Conference on Computer Supported Cooperative Work in Design, 2025
A Single-Loop Fuzzy Simulation-Based Adaptive Kriging Method for Estimating Time-Dependent Failure Possibility.
Int. J. Fuzzy Syst., November, 2024
A double-loop Kriging model algorithm combined with importance sampling for time-dependent reliability analysis.
Eng. Comput., June, 2024
Metamodel-Based Directional Importance Sampling for Structural Reliability Analysis.
IEEE Trans. Reliab., March, 2024
Two-Phase Adaptive Kriging Model Based Importance Sampling Method for Estimating Time-Dependent Failure Probability.
IEEE Trans. Reliab., March, 2024
Survival signature based robust redundancy allocation under imprecise probability.
Reliab. Eng. Syst. Saf., November, 2023
Novel Kriging based learning function for system reliability analysis with correlated failure modes.
Reliab. Eng. Syst. Saf., November, 2023
An efficient hierarchical fuzzy simulation method for estimating failure possibility.
Eng. Comput., October, 2023
Reliability analysis of bending fatigue life of hydraulic pipeline.
Reliab. Eng. Syst. Saf., 2023
An efficient trajectory sampling design method for elementary effect based global sensitivity analysis.
Commun. Stat. Simul. Comput., 2022
Improved chance index and its solutions for quantifying the structural safety degree under twofold random uncertainty.
Reliab. Eng. Syst. Saf., 2021
Fuzzy importance sampling method for estimating failure possibility.
Fuzzy Sets Syst., 2021
Two Efficient AK-Based Global Reliability Sensitivity Methods by Elaborative Combination of Bayes' Theorem and the Law of Total Expectation in the Successive Intervals Without Overlapping.
IEEE Trans. Reliab., 2020
A novel dual-stage adaptive Kriging method for profust reliability analysis.
J. Comput. Phys., 2020
An elaborate algorithm for analyzing the Borgonovo moment-independent sensitivity by replacing the probability density function estimation with the probability estimation.
Reliab. Eng. Syst. Saf., 2019