World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
61
Citations
12512
World Ranking
3120
National Ranking
419

Overview

Hong-Zhong Huang is affiliated with the University of Electronic Science and Technology of China. Their research primarily spans the fields of engineering, decision sciences, and computer science, with a significant focus on reliability engineering and related areas.

The subfields of study that Hong-Zhong Huang contributes to include:

  • Statistics, Probability and Uncertainty
  • Safety, Risk, Reliability and Quality
  • Software
  • Mechanical Engineering
  • Computational Theory and Mathematics

Key topics in their research cover:

  • Probabilistic and Robust Engineering Design
  • Reliability and Maintenance Optimization
  • Software Reliability and Analysis Research
  • Advanced Multi-Objective Optimization Algorithms
  • Risk and Safety Analysis
  • Optimal Experimental Design Methods
  • Structural Health Monitoring Techniques

Hong-Zhong Huang has published extensively in several prominent venues, including:

  • Reliability Engineering & System Safety
  • Journal of Mechanical Science and Technology
  • ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems Part A Civil Engineering
  • Mechanical Systems and Signal Processing
  • IOP Conference Series Materials Science and Engineering

Among their recent publications are:

  • "Time-variant system reliability analysis method for a small failure probability problem" (2020, Reliability Engineering & System Safety)
  • "Time-variant reliability analysis for industrial robot RV reducer under multiple failure modes using Kriging model" (2020, Reliability Engineering & System Safety)
  • "A single-loop strategy for time-variant system reliability analysis under multiple failure modes" (2020, Mechanical Systems and Signal Processing)
  • "Integrated production planning and preventive maintenance scheduling for synchronized parallel machines" (2021, Reliability Engineering & System Safety)
  • "Structural fatigue reliability analysis based on active learning Kriging model" (2023, International Journal of Fatigue)

The scientist has collaborated frequently with coauthors such as Huaming Qian, Yan-Feng Li, Tudi Huang, Yu Liu, and Tao Jiang.

In addition to articles, Hong-Zhong Huang has contributed to book publications, notably within the Springer series in reliability engineering. One such work is "Selective Maintenance Modelling and Optimization," published in 2023.

Best Publications

  • A Bidirectional LSTM Prognostics Method Under Multiple Operational Conditions

    Cheng-Geng Huang;Hong-Zhong Huang;Yan-Feng Li

  • MULTIPLE FAILURE MODES ANALYSIS AND WEIGHTED RISK PRIORITY NUMBER EVALUATION IN FMEA

    Ningcong Xiao;Hong-Zhong Huang;Yanfeng Li;Liping He

  • An efficient method for reliability evaluation of multistate networks given all minimal path vectors

    Ming J. Zuo;Zhigang Tian;Hong-Zhong Huang

  • Optimal reliability, warranty and price for new products

    Hong-Zhong Huang;Zhi-Jie Liu;D. N. P. Murthy

  • Optimal Selective Maintenance Strategy for Multi-State Systems Under Imperfect Maintenance

    Yu Liu;Hong-Zhong Huang

  • Bayesian reliability analysis for fuzzy lifetime data

    Hong-Zhong Huang;Ming J. Zuo;Zhan-Quan Sun

  • Probabilistic Physics of Failure-based framework for fatigue life prediction of aircraft gas turbine discs under uncertainty

    Shun-Peng Zhu;Hong-Zhong Huang;Weiwen Peng;Hai-Kun Wang

  • Reliability analysis of complex multi-state system with common cause failure based on evidential networks

    Jinhua Mi;Yan-Feng Li;Weiwen Peng;Hong-Zhong Huang

  • Risk evaluation in failure mode and effects analysis of aircraft turbine rotor blades using Dempster–Shafer evidence theory under uncertainty

    Jianping Yang;Hong Zhong Huang;Li Ping He;Shun Peng Zhu

  • Inverse Gaussian process models for degradation analysis: A Bayesian perspective

    Weiwen Peng;Yanfeng Li;Yuanjian Yang;Hong-Zhong Huang

  • Posbist fault tree analysis of coherent systems

    Hong-Zhong Huang;Xin Tong;Ming Jian Zuo

  • Toward a Better Understanding of Model Validation Metrics

    Yu Liu;Wei Chen;Paul Arendt;Hong Zhong Huang

  • Bayesian Degradation Analysis With Inverse Gaussian Process Models Under Time-Varying Degradation Rates

    Weiwen Peng;Yan-Feng Li;Yuan-Jian Yang;Jinhua Mi

  • Reliability analysis of a floating offshore wind turbine using Bayesian Networks

    He Li;He Li;C. Guedes Soares;Hong-Zhong Huang

  • Reliability analysis of multi-state systems with common cause failures based on Bayesian network and fuzzy probability

    Yan-Feng Li;Hong-Zhong Huang;Jinhua Mi;Weiwen Peng

  • A novel deep convolutional neural network-bootstrap integrated method for RUL prediction of rolling bearing

    Cheng-Geng Huang;Hong-Zhong Huang;Yan-Feng Li;Weiwen Peng

  • Optimal Replacement Policy for Multi-State System Under Imperfect Maintenance

    Yu Liu;Hong-Zhong Huang

  • Support vector machine based estimation of remaining useful life: current research status and future trends

    Unknown

  • An Approach to Reliability Assessment Under Degradation and Shock Process

    Zhonglai Wang;Hong-Zhong Huang;Yanfeng Li;Ning-Cong Xiao

  • A generalized energy-based fatigue–creep damage parameter for life prediction of turbine disk alloys

    Shun-Peng Zhu;Hong-Zhong Huang;Li-Ping He;Yu Liu

  • Bivariate Analysis of Incomplete Degradation Observations Based on Inverse Gaussian Processes and Copulas

    Weiwen Peng;Yan-Feng Li;Yuan-Jian Yang;Shun-Peng Zhu

  • Reliability assessment of complex electromechanical systems under epistemic uncertainty

    Jinhua Mi;Yan-Feng Li;Yuan-Jian Yang;Weiwen Peng

  • Reliability assessment for fuzzy multi-state systems

    Yu Liu;Hong-Zhong Huang

  • An interactive fuzzy multi-objective optimization method for engineering design

    Hong-Zhong Huang;Ying-Kui Gu;Xiaoping Du

  • Fuzzy multi-objective optimization decision-making of reliability of series system

    H.-Z. Huang

  • Bayesian framework for probabilistic low cycle fatigue life prediction and uncertainty modeling of aircraft turbine disk alloys

    Shun-Peng Zhu;Hong-Zhong Huang;Reuel Smith;Victor Ontiveros

Frequent Co-Authors

Yu Liu
Yu Liu University of Electronic Science and Technology of China
Ming J. Zuo
Ming J. Zuo University of Alberta
Gregory Levitin
Gregory Levitin Southwest Jiaotong University
Enrico Zio
Enrico Zio Polytechnic University of Milan
Min Xie
Min Xie City University of Hong Kong
Maxim Finkelstein
Maxim Finkelstein University of the Free State
Dong Wang
Dong Wang Peking University
Liudong Xing
Liudong Xing University of Massachusetts Dartmouth
Sankaran Mahadevan
Sankaran Mahadevan Vanderbilt University
D. N. P. Murthy
D. N. P. Murthy University of Queensland

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