Load Optimization of E-government System Based on Hiphop-PHP. - Bingyu Ge; Zhiyi Fang; Ce Han; Lei Pu; Quan Zhang; Hong Pei (MISNC, 2014)

A multi-stage Wiener process-based prognostic model for equipment considering the influence of imperfect maintenance activities. - Hong Pei; Xiaosheng Si; Changhua Hu; Zhaoqiang Wang; Dangbo Du; Zhenan Pang (J. Intell. Fuzzy Syst., 2018)

SAR Ship Detection Under Complex Background Based on Attention Mechanism. - Chen Chen 051; Changhua Hu; Chuan He 003; Hong Pei; Zhenan Pang; Tong Zhao (IGTA, 2019)

A Deep Neural Network Based on an Attention Mechanism for SAR Ship Detection in Multiscale and Complex Scenarios. - Chen Chen 051; Chuan He 003; Changhua Hu; Hong Pei; Licheng Jiao (IEEE Access, 2019)

MSARN: A Deep Neural Network Based on an Adaptive Recalibration Mechanism for Multiscale and Arbitrary-Oriented SAR Ship Detection. - Chen Chen 051; Chuan He 003; Changhua Hu; Hong Pei; Licheng Jiao (IEEE Access, 2019)

Nonlinear Step-Stress Accelerated Degradation Modeling and Remaining Useful Life Estimation Considering Multiple Sources of Variability. - Zhenan Pang; Changhua Hu; Xiaosheng Si; Jianxun Zhang 001; Dangbo Du; Hong Pei (IEEE Access, 2019)

Remaining Useful Life Prediction for Nonlinear Degraded Equipment With Bivariate Time Scales. - Hong Pei; Changhua Hu; Xiaosheng Si; Jian-Fei Zheng; Qi Zhang 035; Zhengxin Zhang; Zhenan Pang (IEEE Access, 2019)

An Adaptive Prognostic Approach for Newly Developed System With Three-Source Variability. - Xi Wang; Changhua Hu; Xiaosheng Si; Jian-Fei Zheng; Hong Pei; Yong Yu 013; Ziqiang Ren (IEEE Access, 2019)

A Sequential Bayesian Updated Wiener Process Model for Remaining Useful Life Prediction. - Tianmei Li 001; Hong Pei; Zhenan Pang; Xiaosheng Si; Jian-Fei Zheng (IEEE Access, 2020)

NHPP Testability Growth Model Considering Testability Growth Effort, Rectifying Delay, and Imperfect Correction. - Tianmei Li 001; Xiaosheng Si; Zonghao Yang; Hong Pei; Yuzhe Ma (IEEE Access, 2020)

A Prognostic Model Based on DBN and Diffusion Process for Degrading Bearing. - Chang-Hua Hu; Hong Pei; Xiao-Sheng Si; Dang-Bo Du; Zhenan Pang; Xi Wang (IEEE Trans. Ind. Electron., 2020)

Joint Decision for Spare Part Ordering and Equipment Replacement Based on Prognostic Information. - Hanxiao Mu; Jianfei Zheng; Dangbo Du; Hong Pei; Qing Dong; Bowei Zhang (CAA SAFEPROCESS, 2021)

An adaptive prognostics method for fusing CDBN and diffusion process: Application to bearing data. - Hong Pei; Xiao-Sheng Si; Chang-Hua Hu; Jian-Fei Zheng; Tianmei Li 001; Jianxun Zhang 001; Zhenan Pang (Neurocomputing, 2021)

A Bayesian Inference for Remaining Useful Life Estimation by Fusing Accelerated Degradation Data and Condition Monitoring Data. - Zhenan Pang; Xiaosheng Si; Changhua Hu; Dangbo Du; Hong Pei (Reliab. Eng. Syst. Saf., 2021)

Prognostics based on the generalized diffusion process with parameters updated by a sequential Bayesian method. - Hong Pei; Xiaosheng Si; Changhua Hu; Jianxun Zhang 001; Dangbo Du; Zhenan Pang; Shengfei Zhang (Sci. China Inf. Sci., 2022)

A condition-based prognostic approach for age- and state-dependent partially observable nonlinear degrading system. - Zhenan Pang; Tianmei Li 003; Hong Pei; Xiaosheng Si (Reliab. Eng. Syst. Saf., 2023)

Bayesian Deep-Learning-Based Prognostic Model for Equipment Without Label Data Related to Lifetime. - Hong Pei; Xiao-Sheng Si; Changhua Hu; Tianmei Li 001; Chuan He 003; Zhenan Pang (IEEE Trans. Syst. Man Cybern. Syst., 2023)

Prognosis for stochastic degrading systems with massive data: A data-model interactive perspective. - Tianmei Li 001; Hong Pei; Xiaosheng Si; Yaguo Lei (Reliab. Eng. Syst. Saf., 2023)

A prognostic model for multi-stage degraded equipment under zero life label combining CDBN and Bayesian bidirectional GRU. - Hong Pei; Xiaosheng Si; Zhengxin Zhang; Dangbo Du; Changhua Hu; Xinlong Chang (Adv. Eng. Informatics, 2024)

Lifetime prediction and replacement optimization for a standby system considering storage failures of spare parts. - Jianfei Zheng; Jincheng Ren; Hong Pei; Jianxun Zhang; Zhengxin Zhang (Reliab. Eng. Syst. Saf., 2024)

Remaining useful life prediction method for rolling bearings based on hybrid dilated convolution transfer. - Bo Zhang; Changhua Hu; Hao Zhang; Jianfei Zheng; Jianxun Zhang 001; Hong Pei (Qual. Reliab. Eng. Int., 2024)

Interactive Prognosis Framework Between Deep Learning and a Stochastic Process Model for Remaining Useful Life Prediction. - Hong Pei; Xiaosheng Si; Tianmei Li 001; Zhengxin Zhang; Yaguo Lei (IEEE Trans. Neural Networks Learn. Syst., 2024)

Specifying Quantization Characteristics for Required Lifetime Prognostic Performance. - Qing Dong; Jian-xun Zhang 001; Changhua Hu; Zhengxin Zhang; Dangbo Du; Hong Pei (IEEE Trans. Instrum. Meas., 2025)

MAACCN: An Intelligent Decoupling Diagnosis Method for Compound Faults in Electrohydrostatic Actuators. - Yuanhao Hu; Yibo Song; Xiansong He; Xiaoli Zhao; Xiaowei Yang; Jianyong Yao; Zhaoqiang Wang; Hong Pei; Changhua Hu (IEEE Trans. Instrum. Meas., 2025)

A novel prognostic method for degrading devices with nonlinear degradation processes indexed by both continuous and discrete time scales. - Jianfei Zheng; Xinyue Geng; Changhua Hu; Hong Pei; Zhengxin Zhang (Trans. Inst. Meas. Control, 2025)