Comparison of Neural Network and Kriging Method for Creating Simulation-Optimization Metamodels. - Yuan Ren; Guangchen Bai (DASC, 2009)

Determination of Optimal SVM Parameters by Using GA/PSO. - Yuan Ren; Guangchen Bai (J. Comput., 2010)

Extremum Response Surface Method for Casing Radial Deformation Probabilistic Analysis. - Cheng-Wei Fei; Guangchen Bai; Tian Chao (J. Aerosp. Inf. Syst., 2013)

Dynamic neural network method-based improved PSO and BR algorithms for transient probabilistic analysis of flexible mechanism. - Lu-Kai Song; Cheng-Wei Fei; Guangchen Bai; Lin-Chong Yu (Adv. Eng. Informatics, 2017)

DNN-Based Surrogate Modeling-Based Feasible Performance Reliability Design Methodology for Aircraft Engine. - Dalu Cao; Guangchen Bai (IEEE Access, 2020)

Multi-Surrogate Collaboration Approach for Creep-Fatigue Reliability Assessment of Turbine Rotor. - Lu-Kai Song; Guangchen Bai (IEEE Access, 2020)

A Novel Reliability Analysis Approach With Collaborative Active Learning Strategy-Based Augmented RBF Metamodel. - Yanxu Wei; Guangchen Bai; Lu-Kai Song (IEEE Access, 2020)

An integrated reliability approach with improved importance sampling for low-cycle fatigue damage prediction of turbine disks. - Haifeng Gao; Anjenq Wang; Enrico Zio; Guangchen Bai (Reliab. Eng. Syst. Saf., 2020)

Vectorial surrogate modeling approach for multi-failure correlated probabilistic evaluation of turbine rotor. - Xue-Qin Li; Lu-Kai Song; Guangchen Bai (Eng. Comput., 2023)