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OpenAlex Citation Counts

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OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

Physics-informed recurrent neural networks and hyper-parameter optimization for dynamic process systems
Tuse Asrav, Erdal Aydın
Computers & Chemical Engineering (2023) Vol. 173, pp. 108195-108195
Closed Access | Times Cited: 32

Showing 1-25 of 32 citing articles:

Bayesian machine learning-aided approach bridges between dynamic elasticity and compressive strength in the cement-based mortars
Ning Wang, Majid Samavatian, Vahid Samavatian, et al.
Materials Today Communications (2023) Vol. 35, pp. 106283-106283
Closed Access | Times Cited: 25
Hyperparameter optimization of orthogonal functions in the numerical solution of differential equations
Alireza Afzal Aghaei, Kourosh Parand
Mathematical Methods in the Applied Sciences (2024)
Open Access | Times Cited: 6
Sparse Mass-Constrained Nonlinear Dynamic Model Building from Noisy Data Using a Bayesian Approach
Samuel Adeyemo, Debangsu Bhattacharyya
Industrial & Engineering Chemistry Research (2025)
Closed Access
Integrating Order-of-Magnitude Analysis to Physics-Informed Neural Networks for Linear Chromatographic Models
Yucheng Chen, Shan‐Jing Yao, Dong‐Qiang Lin
Industrial & Engineering Chemistry Research (2025)
Closed Access
Role of the human-in-the-loop in emerging self-driving laboratories for heterogeneous catalysis
Christoph Scheurer, Karsten Reuter
Nature Catalysis (2025) Vol. 8, Iss. 1, pp. 13-19
Closed Access
Biomass and waste plastics chemical looping co-gasification for hydrogen-electricity-DME conservation and recycling based on machine learning
Wende Tian, Shuming Zhang, Shaochen Wang, et al.
Energy (2025), pp. 134868-134868
Closed Access
A review on full-, zero-, and partial-knowledge based predictive models for industrial applications
Stefano Zampini, Guido Parodi, Luca Oneto, et al.
Information Fusion (2025), pp. 102996-102996
Open Access
Physics-Informed and Data-Driven Modeling of an Industrial Wastewater Treatment Plant with Actual Validation
Ece Serenat Koksal, Tuse Asrav, Elif Ecem Esenboga, et al.
Computers & Chemical Engineering (2024) Vol. 189, pp. 108801-108801
Closed Access | Times Cited: 4
Tribological Properties Assessment of Metallic Glasses Through a Genetic Algorithm-Optimized Machine Learning Model
Untung Rahardja, Arif Sarı, Ali Alsalamy, et al.
Metals and Materials International (2023) Vol. 30, Iss. 3, pp. 745-755
Closed Access | Times Cited: 13
Fractional rheology-informed neural networks for data-driven identification of viscoelastic constitutive models
Donya Dabiri, Milad Saadat, Deepak Mangal, et al.
Rheologica Acta (2023) Vol. 62, Iss. 10, pp. 557-568
Open Access | Times Cited: 11
Data-driven modeling for complex contacting phenomena via improved neural networks considering link switches
Jia Ma, Jie Wang, Jing Peng, et al.
Mechanism and Machine Theory (2023) Vol. 191, pp. 105521-105521
Closed Access | Times Cited: 11
Very high cycle fatigue life prediction of Ti60 alloy based on machine learning with data enhancement
Hongjiang Qian, Zhiyong Huang, Yeting Xu, et al.
Engineering Fracture Mechanics (2023) Vol. 289, pp. 109431-109431
Closed Access | Times Cited: 10
Dynamic Domino Effect Assessment (D2EA) in tank farms using a machine learning-based approach
Md. Tanjin Amin, Giordano Emrys Scarponi, Valerio Cozzani, et al.
Computers & Chemical Engineering (2023) Vol. 181, pp. 108556-108556
Closed Access | Times Cited: 8
Modeling the anaerobic digestion of palm oil mill effluent via physics-informed deep learning
Kar Ming Shaw, Phaik Eong Poh, Yong Kuen Ho, et al.
Chemical Engineering Journal (2024) Vol. 485, pp. 149826-149826
Open Access | Times Cited: 2
Physics‐informed learning of chemical reactor systems using decoupling–coupling training framework
Zhi‐Yong Wu, Mingjian Li, Chang He, et al.
AIChE Journal (2024) Vol. 70, Iss. 7
Closed Access | Times Cited: 2
Artificial intelligence and machine learning at various stages and scales of process systems engineering
Karthik K. Srinivasan, Anjana Puliyanda, Devavrat Thosar, et al.
The Canadian Journal of Chemical Engineering (2024) Vol. 103, Iss. 3, pp. 1004-1035
Open Access | Times Cited: 2
Advances on hybrid modelling for bioprocesses engineering: insights into research trends and future directions from a bibliometric approach
Juan Federico Herrera-Ruiz, Javier Fontalvo, Oscar Andrés Prado-Rúbio
Results in Engineering (2024), pp. 103548-103548
Open Access | Times Cited: 2
Dynamic optimal control of coal tar chemical looping gasification based on process modelling and intelligent screening
Zhe Li, Zijian Liu, Shaochen Wang, et al.
Journal of Cleaner Production (2024) Vol. 444, pp. 141266-141266
Closed Access | Times Cited: 1
Novel approaches for hyper-parameter tuning of physics-informed Gaussian processes: application to parametric PDEs
Masoud Ezati, Mohsen Esmaeilbeigi, Ahmad Kamandi
Engineering With Computers (2024) Vol. 40, Iss. 5, pp. 3175-3194
Closed Access | Times Cited: 1
Reloading Process Systems Engineering within Chemical Engineering
Vassilios S. Vassiliadis, Vasileios Mappas, T.A. Espaas, et al.
Process Safety and Environmental Protection (2024) Vol. 209, pp. 380-398
Closed Access | Times Cited: 1
Hybrid Modeling of Fed-Batch Cell Culture Using Physics-Informed Neural Network
Shu Yang, William Fahey, Brendha Truccollo, et al.
Industrial & Engineering Chemistry Research (2024)
Closed Access | Times Cited: 1
Predicting reactivity dynamics of halogen species and trace organic contaminants using machine learning models
Jingyi Zhu, Yuanxi Huang, Qihang Yi, et al.
Chemosphere (2023) Vol. 346, pp. 140659-140659
Closed Access | Times Cited: 3
A physics-informed long short-term memory (LSTM) model for estimating ammonia emissions from dairy manure during storage
Rana A. Genedy, Matthias Chung, Julie Shortridge, et al.
The Science of The Total Environment (2023) Vol. 912, pp. 168885-168885
Closed Access | Times Cited: 3
A novel approach to aeroengine performance diagnosis based on physical model coupling data-driven using low-rank multimodal fusion method
Zepeng Wang, Ye Wang, Xizhen Wang, et al.
Journal of the Global Power and Propulsion Society (2024) Vol. 8, pp. 334-348
Open Access
Otimização de Hiperparâmetros de Redes Neurais guiadas pela Física em Problema Convectivo-Difusivo
Ricardo Ervilha Silva, José J. Camata
(2024), pp. 137-144
Open Access
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