Gyula Dörgő
Gyula Dörgő
MTA-PE Lendület Complex Systems Monitoring Research Group
E-mail megerősítve itt: fmt.uni-pannon.hu - Kezdőlap
Hivatkozott rá
Hivatkozott rá
Evaluating the Interconnectedness of the Sustainable Development Goals Based on the Causality Analysis of Sustainability Indicators
G Dörgő, V Sebestyén, J Abonyi
Sustainability 10 (10), 3766, 2018
Review and structural analysis of system dynamics models in sustainability science
G Honti, G Dörgő, J Abonyi
Journal of Cleaner Production 240, 118015, 2019
Sequence mining based alarm suppression
G Dorgo, J Abonyi
IEEE Access 6, 15365-15379, 2018
Decision trees for informative process alarm definition and alarm-based fault classification
G Dorgo, A Palazoglu, J Abonyi
Process Safety and Environmental Protection 149, 312-324, 2020
Learning and predicting operation strategies by sequence mining and deep learning
G Dorgo, J Abonyi
Computers & Chemical Engineering 128, 174-187, 2019
Understanding the importance of process alarms based on the analysis of deep recurrent neural networks trained for fault isolation
G Dorgo, P Pigler, J Abonyi
Journal of Chemometrics 32 (4), e3006, 2018
P-graph-based multi-objective risk analysis and redundancy allocation in safety-critical energy systems
Z Süle, J Baumgartner, G Dörgő, J Abonyi
Energy 179, 989-1003, 2019
Directions of membrane separator development for microbial fuel cells: A retrospective analysis using frequent itemset mining and descriptive statistical approach
L Koók, G Dörgő, P Bakonyi, T Rózsenberszki, N Nemestóthy, ...
Journal of Power Sources 478, 229014, 2020
Fuzzy activity time-based model predictive control of open-station assembly lines
T Ruppert, G Dorgo, J Abonyi
Journal of Manufacturing Systems 54, 12-23, 2020
Automated Analysis of the Interactions Between Sustainable Development Goals Extracted from Models and Texts of Sustainability Science
G Dorgo, G Honti, J Abonyi
Chemical Engineering Transactions 70, 781-786, 2018
Hierarchical frequent sequence mining algorithm for the analysis of alarm cascades in chemical processes
G Dorgo, K Varga, J Abonyi
IEEE Access 6, 50197-50216, 2018
Quality vs. quantity of alarm messages-How to measure the performance of an alarm system
G Dorgo, F Tandari, T Szabó, A Palazoglu, J Abonyi
Chemical Engineering Research and Design 173, 63-80, 2021
Learning operation strategies from alarm management systems by temporal pattern mining and deep learning
G Dorgo, P Pigler, M Haragovics, J Abonyi
Computer Aided Chemical Engineering 43, 1003-1008, 2018
Processing indoor positioning data by goal-oriented supervised fuzzy clustering for tool management
A Darányi, G Dörgő, T Ruppert, J Abonyi
Journal of Manufacturing Systems 63, 15-22, 2022
Network analysis dataset of system dynamics models
G Honti, G Dörgő, J Abonyi
Data in brief 27, 2019
Sparse PCA Support Exploration of Process Structures for Decentralized Fault Detection
M Theisen, G Dörgő, J Abonyi, A Palazoglu
Industrial & Engineering Chemistry Research 60 (22), 8183-8195, 2021
Event-Tree Based Sequence Mining Using LSTM Deep-Learning Model
J Abonyi, R Károly, G Dörgő
Complexity 2021, 2021
Process mining in production systems
J Abonyi, G Dorgo
2019 IEEE 23rd International Conference on Intelligent Engineering Systems …, 2019
Towards Operator 4.0, Increasing Production Efficiency and Reducing Operator Workload by Process Mining of Alarm Data
G Dorgo, K Varga, M Haragovics, T Szabo, J Abonyi
Chemical Engineering Transactions 70, 829-834, 2018
Comparison of the effects of thermal pretreatment, steam explosion and ultrasonic disintegration on digestibility of corn stover
D Capári, G Dörgő, A Dallos
Journal of Sustainable Development of Energy, Water and Environment Systems …, 2016
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