OOIR: Observatory of International Research

Papers

(The H4-Index of Computers & Chemical Engineering is 37. The table below lists those papers that are above that threshold based on CrossRef citation counts [max. 250 papers]. The publications cover those that have been published in the past four years, i.e., from 2020-09-01 to 2024-09-01.)

Article	Citations
Process systems engineering – The generation next?	150
Recent trends on hybrid modeling for Industry 4.0	139
A deep reinforcement learning approach for chemical production scheduling	105
Green hydrogen for industrial sector decarbonization: Costs and impacts on hydrogen economy in qatar	94
An analysis of process fault diagnosis methods from safety perspectives	92
Crude oil price prediction: A comparison between AdaBoost-LSTM and AdaBoost-GRU for improving forecasting performance	92
A review on robust M-estimators for regression analysis	86
Recent developments on sewage sludge pyrolysis and its kinetics: Resources recovery, thermogravimetric platforms, and innovative prospects	86
Deep learning and knowledge-based methods for computer-aided molecular design—toward a unified approach: State-of-the-art and future directions	79
Fault detection and identification using Bayesian recurrent neural networks	78
Reinforcement learning based optimal control of batch processes using Monte-Carlo deep deterministic policy gradient with phase segmentation	73
LDA-based deep transfer learning for fault diagnosis in industrial chemical processes	66
Perspectives on the integration between first-principles and data-driven modeling	65
Power-to-X: A review and perspective	64
Considerations, challenges and opportunities when developing data-driven models for process manufacturing systems	61
Performance prediction of trace metals and cod in wastewater treatment using artificial neural network	59
Molecular insights through computational modeling of methylene blue adsorption onto low-cost adsorbents derived from natural materials: A multi-model's approach	56
Air catalytic biomass (PKS) gasification in a fixed-bed downdraft gasifier using waste bottom ash as catalyst with NARX neural network modelling	56
Reinforcement learning approach to autonomous PID tuning	56
A tutorial review of neural network modeling approaches for model predictive control	55
Real-time optimization using reinforcement learning	52
An extended Tennessee Eastman simulation dataset for fault-detection and decision support systems	51
Self-adaptive deep learning for multimode process monitoring	50
Challenges and opportunities in carbon capture, utilization and storage: A process systems engineering perspective	49
Feature engineering in big data analytics for IoT-enabled smart manufacturing – Comparison between deep learning and statistical learning	48

Surrogate-based optimization for mixed-integer nonlinear problems	48
Hybrid Modeling in the Era of Smart Manufacturing	46
On-line classification of coal combustion quality using nonlinear SVM for improved neural network NOx emission rate prediction	42
Quantum computing assisted deep learning for fault detection and diagnosis in industrial process systems	42
Risk-based fault prediction of chemical processes using operable adaptive sparse identification of systems (OASIS)	41
One step forward for smart chemical process fault detection and diagnosis	41
Modeling and simulation for design and analysis of membrane-based separation processes	41
Fast approximate learning-based multistage nonlinear model predictive control using Gaussian processes and deep neural networks	40
Blast furnace hot metal temperature and silicon content prediction using soft sensor based on fuzzy C-means and exogenous nonlinear autoregressive models	39
Biomass waste-to-energy supply chain optimization with mobile production modules	39
Sustainable wastewater treatment plants design through multiobjective optimization	39
Hybrid machine learning assisted modelling framework for particle processes	37