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Journal of Process Control
H-index 31

Journal of Process Control

Ranking & Metrics

Discipline name Position Best Scientists Publications D-Index
Electronics and Electrical Engineering 151 69 146 23
Mechanical and Aerospace Engineering 308 12 21 8
Engineering and Technology 390 53 90 20

Additional Metrics

Number of Best Scientists*: 168
Documents by Best Scientists*: 292
Top 100 Ranked Scientists*: 9
SCIMAGO H-index: 133
SCIMAGO SJR: 0.869
Impact Factor: 3.9

Overview

Top Research Topics at Journal of Process Control?

The journal was organized to reinforce research efforts on Control theory, Nonlinear system, Control engineering, Control theory and Model predictive control. Journal of Process Control investigates Control theory research which frequently intersects with Mathematical optimization. Presentations on Mathematical optimization include those discussing Optimization problem and Optimal control.

Nonlinear system research featured in it incorporates concerns from various other topics such as Observer (quantum physics) and Algorithm. Some problems in Control engineering that were presented in it overlapped with concepts under Process control and Control (management). The journal explores research in Control theory and the adjacent study of Stability (learning theory).

  • Control theory (59.48%)
  • Nonlinear system (21.24%)
  • Control engineering (20.85%)

What are the most cited papers published in the journal?

  • Simple analytic rules for model reduction and PID controller tuning (1413 citations)
  • Survey of robust residual generation and evaluation methods in observer-based fault detection systems (1105 citations)
  • Architectures for distributed and hierarchical Model Predictive Control - A review (1011 citations)

Research areas of the most cited articles at Journal of Process Control:

The published papers mainly deal with areas of study such as Control theory, Control engineering, Model predictive control, Nonlinear system and Mathematical optimization. The journal articles deal with Control engineering in conjunction with Fault detection and isolation and similar fields in Machine learning. The journal articles tackle studies in Benchmark (computing) and the interrelated subject of Fault (power engineering) to gain insights into Model predictive control.

What topics the last edition of the journal is best known for?

  • Statistics
  • Artificial intelligence
  • Mechanical engineering

The previous edition focused in particular on these issues:

The journal mostly deals with topics like Control theory, Nonlinear system, Algorithm, Model predictive control and Control theory. The Control theory research presented places emphasis on topics like Observer (quantum physics), Observability, Multivariable calculus, Kalman filter and Extended Kalman filter. The journal explores topics in Nonlinear system which can be helpful for research in disciplines like Artificial neural network, Convergence (routing), Optimization problem, Setpoint and Performance improvement.

The research on Algorithm featured in it combines topics in other fields like State vector, Principal component analysis, Key (cryptography) and Fault detection and isolation. Issues in Model predictive control were discussed, taking into consideration concepts from other disciplines like Layer (object-oriented design), Scalability and Mathematical optimization, Optimal control. The studies in Control theory featured incorporate elements of Exponential stability, Range (statistics), Fuzzy logic, Benchmark (computing) and Process engineering.

The most cited articles from the last journal are:

  • ANN model adaptation algorithm based on extended Kalman filter applied to pH control using MPC (3 citations)
  • Soft-sensor design via task transferred just-in-time-learning coupled transductive moving window learner (3 citations)
  • Bayesian network for dynamic variable structure learning and transfer modeling of probabilistic soft sensor (3 citations)

Papers citation over time

A key indicator for each journal is its effectiveness in reaching other researchers with the papers published at that venue.

The chart below presents the interquartile range (first quartile 25%, median 50% and third quartile 75%) of the number of citations of articles over time.

The top authors publishing in Journal of Process Control (based on the number of publications) are:

  • Biao Huang (81 papers) published 3 papers at the last edition the same number as at the previous edition,
  • Sirish L. Shah (38 papers) absent at the last edition,
  • Furong Gao (34 papers) absent at the last edition,
  • S. Joe Qin (32 papers) absent at the last edition,
  • Sigurd Skogestad (31 papers) absent at the last edition.

The overall trend for top authors publishing in this journal is outlined below. The chart shows the number of publications at each edition of the journal for top authors.

Only papers with recognized affiliations are considered

The top affiliations publishing in Journal of Process Control (based on the number of publications) are:

  • University of Alberta (161 papers) published 5 papers at the last edition, 2 less than at the previous edition,
  • Zhejiang University (98 papers) published 8 papers at the last edition the same number as at the previous edition,
  • Norwegian University of Science and Technology (72 papers) published 3 papers at the last edition the same number as at the previous edition,
  • National University of Singapore (54 papers) published 1 paper at the last edition,
  • Indian Institute of Technology Bombay (52 papers) published 2 papers at the last edition, 1 less than at the previous edition.

The overall trend for top affiliations publishing in this journal is outlined below. The chart shows the number of publications at each edition of the journal for top affiliations.

Publication chance based on affiliation

The publication chance index shows the ratio of articles published by the best research institutions in the journal edition to all articles published within that journal. The best research institutions were selected based on the largest number of articles published during all editions of the journal.

The chart below presents the percentage ratio of articles from top institutions (based on their ranking of total papers).Top affiliations were grouped by their rank into the following tiers: top 1-10, top 11-20, top 21-50, and top 51+. Only articles with a recognized affiliation are considered.

During the most recent 2021 edition, 10.92% of publications had an unrecognized affiliation. Out of the publications with recognized affiliations, 25.47% were posted by at least one author from the top 10 institutions publishing in the journal. Another 8.49% included authors affiliated with research institutions from the top 11-20 affiliations. Institutions from the 21-50 range included 15.09% of all publications and 50.94% were from other institutions.

Returning Authors Index

A very common phenomenon observed among researchers publishing scientific articles is the intentional selection of journals they have already attended in the past. In particular, it is worth analyzing the case when the authors participate in the same journal from year to year.

The Returning Authors Index presented below illustrates the ratio of authors who participated in both a given as well as the previous edition of the journal in relation to all participants in a given year.

Returning Institution Index

The graph below shows the Returning Institution Index, illustrating the ratio of institutions that participated in both a given and the previous edition of the conference in relation to all affiliations present in a given year.

The experience to innovation index

Our experience to innovation index was created to show a cross-section of the experience level of authors publishing in a journal. The index includes the authors publishing at the last edition of a journal, grouped by total number of publications throughout their academic career (P) and the total number of citations of these publications ever received (C).

The group intervals were selected empirically to best show the diversity of the authors' experiences, their labels were selected as a convenience, not as judgment. The authors were divided into the following groups:

  • Novice - P < 5 or C < 25 (the number of publications less than 5 or the number of citations less than 25),
  • Competent - P < 10 or C < 100 (the number of publications less than 10 or the number of citations less than 100),
  • Experienced - P < 25 or C < 625 (the number of publications less than 25 or the number of citations less than 625),
  • Master - P < 50 or C < 2500 (the number of publications less than 50 or the number of citations less than 2500),
  • Star - P ≥ 50 and C ≥ 2500 (both the number of publications greater than 50 and the number of citations greater than 2500).

The chart below illustrates experience levels of first authors in cases of publications with multiple authors.

Top Publications

  • Deep learning for fault-relevant feature extraction and fault classification with stacked supervised auto-encoder

    Yalin Wang;Haibing Yang;Xiaofeng Yuan;Yuri A.W. Shardt

    (2020)
    114 Citations
  • Process structure-based recurrent neural network modeling for model predictive control of nonlinear processes

    Zhe Wu;David Rincon;Panagiotis D. Christofides

    (2020)
    104 Citations
  • A survey and classification of incipient fault diagnosis approaches

    H. Safaeipour;M. Forouzanfar;A. Casavola

    (2021)
    103 Citations
  • Rebooting data-driven soft-sensors in process industries: A review of kernel methods

    Yiqi Liu;Yiqi Liu;Min Xie

    (2020)
    95 Citations
  • Cloud-based implementation of white-box model predictive control for a GEOTABS office building: A field test demonstration

    Ján Drgoňa;Ján Drgoňa;Damien Picard;Lieve Helsen

    (2020)
    84 Citations
  • A comprehensive hybrid first principles/machine learning modeling framework for complex industrial processes

    Bei Sun;Chunhua Yang;Yalin Wang;Weihua Gui

    (2020)
    76 Citations
  • A novel virtual sample generation method based on a modified conditional Wasserstein GAN to address the small sample size problem in soft sensing

    Unknown

    (2022)
    69 Citations
  • Graph convolutional network soft sensor for process quality prediction

    (2023)
    58 Citations
  • On Recurrent Neural Networks for learning-based control: recent results and ideas for future developments

    (2021)
    53 Citations
  • Monitoring multimode processes: A modified PCA algorithm with continual learning ability

    Jingxin Zhang;Donghua Zhou;Donghua Zhou;Maoyin Chen

    (2021)
    53 Citations

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