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D-Index & Metrics

Engineering and Technology

D-Index
39
Citations
5560
World Ranking
7752
National Ranking
1387

Overview

Qunxiong Zhu is affiliated with Beijing University of Chemical Technology in China and has a focused research career primarily in the fields of Engineering and Computer Science. Their scholarly output spans over numerous topics, especially in Control and Systems Engineering and Artificial Intelligence, alongside contributions to Mechanical Engineering, Analytical Chemistry, and Industrial and Manufacturing Engineering.

The researcher has contributed extensively to several key research topics including:

  • Fault Detection and Control Systems
  • Mineral Processing and Grinding
  • Spectroscopy and Chemometric Analyses
  • Advanced Algorithms and Applications
  • Machine Learning and ELM
  • Industrial Vision Systems and Defect Detection
  • Anomaly Detection Techniques and Applications

Qunxiong Zhu's work has been published in a variety of recurrent venues such as:

  • IEEE Transactions on Industrial Informatics
  • Industrial & Engineering Chemistry Research
  • IEEE Transactions on Instrumentation and Measurement
  • ISA Transactions
  • Journal of Process Control

Their recent papers include:

  • Novel manifold learning based virtual sample generation for optimizing soft sensor with small data, 2020, ISA Transactions
  • Fault diagnosis using novel AdaBoost based discriminant locality preserving projection with resamples, 2020, Engineering Applications of Artificial Intelligence
  • Novel virtual sample generation using conditional GAN for developing soft sensor with small data, 2021, Engineering Applications of Artificial Intelligence
  • Novel double-layer bidirectional LSTM network with improved attention mechanism for predicting energy consumption, 2021, ISA Transactions
  • Novel soft sensor development using echo state network integrated with singular value decomposition: Application to complex chemical processes, 2020, Chemometrics and Intelligent Laboratory Systems

The scientist collaborates frequently with several co-authors, most notably:

  • Yan-Lin He
  • Yuan Xu
  • Ning Zhang
  • Wei Ke

The range of topics, co-authors, and publication venues reflect a multifaceted research profile with an emphasis on developing and optimizing fault detection systems and soft sensors using machine learning approaches. This is underpinned by practical applications in chemical engineering processes and energy consumption prediction models.

Best Publications

  • Review: Multi-objective optimization methods and application in energy saving

    Yunfei Cui;Yunfei Cui;Zhiqiang Geng;Zhiqiang Geng;Qunxiong Zhu;Qunxiong Zhu;Yongming Han;Yongming Han

  • Energy efficiency analysis method based on fuzzy DEA cross-model for ethylene production systems in chemical industry

    Yongming Han;Yongming Han;Zhiqiang Geng;Zhiqiang Geng;Qunxiong Zhu;Qunxiong Zhu;Yixin Qu

  • A Monte Carlo and PSO based virtual sample generation method for enhancing the energy prediction and energy optimization on small data problem: An empirical study of petrochemical industries

    Hong-Fei Gong;Hong-Fei Gong;Zhong-Sheng Chen;Zhong-Sheng Chen;Qun-Xiong Zhu;Qun-Xiong Zhu;Yan-Lin He;Yan-Lin He

  • Adding rectifying/stripping section type heat integration to a pressure-swing distillation (PSD) process

    Kejin Huang;Lan Shan;Qunxiong Zhu;Jixin Qian

  • Fuzzy multi-attribute decision-making method based on eigenvector of fuzzy attribute evaluation space

    Unknown

  • A Novel Hybrid Method Integrating ICA-PCA With Relevant Vector Machine for Multivariate Process Monitoring

    Yuan Xu;Sheng-Qi Shen;Yan-Lin He;Qun-Xiong Zhu

  • Data driven soft sensor development for complex chemical processes using extreme learning machine

    Yan-Lin He;Yan-Lin He;Zhi-Qiang Geng;Zhi-Qiang Geng;Qun-Xiong Zhu;Qun-Xiong Zhu

  • Novel manifold learning based virtual sample generation for optimizing soft sensor with small data

    Xiao-Han Zhang;Yuan Xu;Yan-Lin He;Yan-Lin He;Qun-Xiong Zhu;Qun-Xiong Zhu

  • Novel virtual sample generation using conditional GAN for developing soft sensor with small data

    Qun-Xiong Zhu;Kun-Rui Hou;Zhong-Sheng Chen;Zi-Shu Gao

  • Energy saving and prediction modeling of petrochemical industries: A novel ELM based on FAHP

    ZhiQiang Geng;ZhiQiang Geng;Lin Qin;Lin Qin;YongMing Han;YongMing Han;QunXiong Zhu;QunXiong Zhu

  • Energy and environment efficiency analysis based on an improved environment DEA cross-model: Case study of complex chemical processes

    ZhiQiang Geng;ZhiQiang Geng;JunGen Dong;JunGen Dong;YongMing Han;YongMing Han;QunXiong Zhu;QunXiong Zhu

  • Multiscale Nonlinear Principal Component Analysis (NLPCA) and Its Application for Chemical Process Monitoring

    Zhiqiang Geng;Qunxiong Zhu

  • Novel double-layer bidirectional LSTM network with improved attention mechanism for predicting energy consumption.

    Yan-Lin He;Lei Chen;Yanlu Gao;Jia-Hui Ma

  • A novel virtual sample generation method based on a modified conditional Wasserstein GAN to address the small sample size problem in soft sensing

    Unknown

  • Multi-objective Particle Swarm Optimization Hybrid Algorithm: An Application on Industrial Cracking Furnace

    Chengfei Li;Qunxiong Zhu;Zhiqiang Geng

  • Design and control of an ideal heat-integrated distillation column (ideal HIDIC) system separating a close-boiling ternary mixture

    Kejin Huang;Lan Shan;Qunxiong Zhu;Jixin Qian

  • Fault diagnosis using novel AdaBoost based discriminant locality preserving projection with resamples

    Yan-Lin He;Yan-Lin He;Yang Zhao;Yang Zhao;Xiao Hu;Xiao Hu;Xiao-Na Yan;Xiao-Na Yan

  • A novel and effective nonlinear interpolation virtual sample generation method for enhancing energy prediction and analysis on small data problem: A case study of Ethylene industry

    Yan-Lin He;Yan-Lin He;Ping-Jiang Wang;Ping-Jiang Wang;Ming-Qing Zhang;Ming-Qing Zhang;Qun-Xiong Zhu;Qun-Xiong Zhu

  • Novel soft sensor development using echo state network integrated with singular value decomposition: Application to complex chemical processes

    Yan-Lin He;Yan-Lin He;Ye Tian;Ye Tian;Yuan Xu;Yuan Xu;Qun-Xiong Zhu;Qun-Xiong Zhu

  • Improved Locality Preserving Projections Based on Heat-Kernel and Cosine Weights for Fault Classification in Complex Industrial Processes

    Unknown

  • Rough set-based heuristic hybrid recognizer and its application in fault diagnosis

    Zhiqiang Geng;Qunxiong Zhu

  • Text Classification Using Novel Term Weighting Scheme-Based Improved TF-IDF for Internet Media Reports

    Zhiying Jiang;Zhiying Jiang;Bo Gao;Bo Gao;Yanlin He;Yanlin He;Yongming Han;Yongming Han

  • Review: Energy efficiency evaluation of complex petrochemical industries

    Yongming Han;Yongming Han;Hao Wu;Hao Wu;Zhiqiang Geng;Zhiqiang Geng;Qunxiong Zhu;Qunxiong Zhu

  • Energy optimization and prediction of complex petrochemical industries using an improved artificial neural network approach integrating data envelopment analysis

    Yong-Ming Han;Yong-Ming Han;Zhi-Qiang Geng;Zhi-Qiang Geng;Qun-Xiong Zhu;Qun-Xiong Zhu

  • Energy management and optimization modeling based on a novel fuzzy extreme learning machine: Case study of complex petrochemical industries

    Yongming Han;Yongming Han;Qing Zeng;Qing Zeng;Zhiqiang Geng;Zhiqiang Geng;Qunxiong Zhu;Qunxiong Zhu

Frequent Co-Authors

Zhiqiang Geng
Zhiqiang Geng Beijing University of Chemical Technology
Abbas Rajabifard
Abbas Rajabifard University of Melbourne
Gao Huang
Gao Huang Tsinghua University
Nengcheng Chen
Nengcheng Chen Wuhan University
Nael H. El-Farra
Nael H. El-Farra University of California, Davis
Ahmet Palazoglu
Ahmet Palazoglu University of California, Davis
Zoltan K. Nagy
Zoltan K. Nagy Purdue University West Lafayette

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