Advanced data mining techniques and model based algorithms in product and process development  Page description

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Details of project

  
Identifier
49534
Type K
Principal investigator Abonyi, János
Title in Hungarian Korszerű adatelemzési technikák és modell alapú algoritmusok a kísérlettervezésben és kiértékelésben
Title in English Advanced data mining techniques and model based algorithms in product and process development
Panel Informatics and Electrical Engineering
Department or equivalent Department of Chemical and Process Engineering (University of Pannonia)
Participants Árva, Péter
Chován, Tibor
Feil, Balázs
Lakatos, Béla
Nagy, Lajos
Németh, Sándor
Szeifert, Ferenc
Starting date 2005-10-01
Closing date 2008-09-30
Funding (in million HUF) 11.760
FTE (full time equivalent) 2.56
state closed project





 

Final report

  
Results in Hungarian
A kutatás során egy termék- és technológiafejlesztési keretrendszer került kidolgozásra a tágabb értelemben vett kísérlettervezési és adatelemzési technikák célirányos fejlesztése alapján. A kidolgozott technikák közös jellemzője a technológia fejlesztés lépései során keletkező információk hatékony kezelése. A technológia üzemeltetése során keletkező adatokból a potenciálisan hasznos információk feltárására adatbányászati technikákat alkalmaztunk, melyeket a vegyészmérnöki, és természettudományos ismeretek hatékony kezelése érdekében a legkorszerűbb folyamat szimulációs eszközökkel integráltunk. Az eredményeket egy a Springer leányvállalatánál (Birkhauser) megjelent monográfiában, egy magyar nyelvű (tan)könyvben, és tíznél több nemzetközi referált folyóiratban publikáltuk. A kidolgozott keretrendszer ipari alkalmazása folyamatban van.
Results in English
A new framework for product and process development has been worked out based on the research of novel data mining and experiment design algorithms. The common feature of the proposed tools and methodologies is the effective management of the information through the whole life-cycle of process development. In the proposed framework data mining techniques have been applied to extract potentially useful information from historical process data. The related process-relevant a priori information is incorporated by advanced simulation techniqes. The resullts has been published in a reserch monogaph by Biskhauser and in more than ten peer-reviewed journals. The industrial application of the proposed framework has been also studied.
Full text http://real.mtak.hu/1991/
Decision
Yes





 

List of publications

  
Balazs Feil, Balazs Balasko, Janos Abonyi: Visualization of Fuzzy Clusters by Fuzzy Sammon Mapping Projection – Application to the Analysis of Phase Space Trajectories, Soft Computing - A Fusion of Foundations, Methodologies and Applications, 2007
Vathy-Fogarassy, A. & Kiss, A. & Abonyi, J.: Topology Representing Network Map - A new Tool for Visualization of High-Dimensional Data, LNCS: Transactions on Computational Science I., Springer-Verlag, 2008
F.P. Pach, B. Balasko, S. Nemeth, P. Arva, J. Abonyi: Black-Box and First-Principle Model Based Optimization of Operating Technologies, 5th MATHMOD Conference, Vienna, 2006
Balaskó B., Németh S., Abonyi J.: Epizód alapú adatelemzési technika technológia-üzemeltetési stratégiák elemzésére, 34. Műszaki Kémiai Napok, Veszprém, 2006
Balaskó B., Németh S., Abonyi J.: Működő technológia optimalizálása az irányító rendszer modelljének felhasználásával, Acta Agraria Kaposváriensis, 2007
B. Balasko, S. Nemeth and J. Abonyi: Analysis of Segmeted Time Series by Sequence Alignment, 7th International Conference of Hungarian Researchers on Computational Intelligence, Budapest, 2006
T. Kenesei, B. Balasko, J. Abonyi: A MATLAB Toolbox and its Web-based Variant for Fuzzy Cluster Analysis, 7th International Conference of Hungarian Researchers on Computational Intelligence, Budapest, 2006
Tamas Kenesei, Balazs Feil, Janos Abonyi: Identification of Hinging Hyperplane Models by Fuzzy c-Regression Clustering, 7th International Conference of Hungarian Researchers on Computational Intelligence, Budapest, 2006
F. P. Pach, A. Gyenesei, P. Arva, J. Abonyi: Fuzzy Association Rule Mining for Model Structure Identification, Applications of Soft Computing: Recent Trends, Springer, 2006
F. P. Pach, B. Feil, S. Nemeth, P. Arva, J. Abonyi: Process Data Warehousing Based Operator Support System for Complex Production Technologies, IEEE Transactions on Systems Man and Cybernetics, Part A: Systems and Humans, Special Issue on Emerging Approaches to Integrating Distributed, Heterogenous, and Complex S, 2006
F. P. Pach, F. Szeifert, S. Nemeth, P. Arva, J. Abonyi: Fuzzy association rule mining for data-driven analysis of dynamical systems, Hungarian Journal of Industrial Chemistry, Special Issue on Recent advances in Computer Aided Process Engineering, 2006
F. D. Tamás, F. P. Pach, J. Abonyi: Analysis of Trace Elements in Clinker based on Supervised Clustering and Fuzzy Association Rule Mining, 12th International Congress on the Chemistry of Cement, Montreal, Canada, 2007
P. Matyus, F. P. Pach, J. Abonyi, A. Gyenesei: Visualization of Fuzzy Association Rules Representing High-Dimensional Problems, 11th IPMU International Conference, 2006
Pach F.P., Gyenesei A., Németh S., Árva P., Abonyi J.: A partícionálás hatása fuzzy asszociatív osztályozók, Acta Agraria Kaposvariensis, 2007
Pach F.P., Németh S., Árva P., Abonyi J.: Szabálybázis alapú módszerek polimerizációs technológiák elemzésére, 34. Műszaki Kémiai Napok, 2006
F. P. Pach, J. Abonyi: Association Rule and Decision Tree based Methods for Fuzzy Rule Base Generation, Enformatika (Transactions on Engineering, Computing and Technology), 2006
Vathy-Fogarassy, A. & Kiss, A. & Abonyi, J.: Improvement of Jarvis-Patrick Clustering, Lecture Notes on AI, Springer (Proceedings of International Workshop on Fuzzy Logic and Applications (WILF 2007)), 2007
Varga, Tamás & Szeifert, Ferenc & Réti, József & Abonyi, János: Analysis of the runaway in an industrial heterocatalytic reactor, omputer-Aided Chemical Engineering (Book chapter based on a Conference Proceedings), Editor: Plesu, Valentin & Serban Agachi, Paul, 2007
Balaskó, Balázs & Németh, Sándor & Abonyi, János: Process Modeling and Simulation for Optimization of Operating Processes, omputer-Aided Chemical Engineering (Book chapter based on a Conference Proceedings), Editor: Plesu, Valentin & Serban Agachi, Paul, 2007
Kenesei, T & Feil, B & Abonyi, J: Fuzzy clustering for the Identification of Hinging Hyperplanes based Regression Trees, Lecture Notes on AI, Springer, Proceedings of International Workshop on Fuzzy Logic and Applications (WILF 2007), 2007
Kenesei, T. & Feil, B. & Abonyi, J.: Hinging Hyperplane Model based Control of Hammerstein Systems, 35. Műszaki Kémiai Napok", 2007
Kenesei, Tamas & Feil, Balazs & Abonyi, Janos: Identification of Dynamic Systems by Hinging Hyperplane Models, 7th International Conference on Applied Informatics, 2007
Kenesei, Tamas & Feil, Balazs & Abonyi, Janos: Identification of Dynamic Systems by Hinging Hyperplane Models, 7th International Conference on Applied Informatics, 2007
Balaskó, Balázs & Németh, Sándor & Abonyi, János: Hierarchical clustering of product transition strategies based on symbolic trend representation in a multi-product process, Műszaki Kémiai Napok '07, 2007
Balaskó, Balázs & Bankó, Zoltán & Abonyi, János: Analyzing Trends by Symbolic Episode Representation and Sequence Alignment, 15th Mediterranean Conference on Automation and Control, 2007
A. Vathy-Fogarassy & A. Werner-Stark & B. Gal & J. Abonyi: Visualization of Topology Representing Networks, Lecture Notes in Computer Science series, ntelligent Data Engineering and Automated Learning - IDEAL 2007, 2007
Pach, FP; Gyenesei, A; Abonyi, J: Compact fuzzy association rule-based classifier, EXPERT SYSTEMS WITH APPLICATIONS Volume: 34 Issue: 4 Pages: 2406-2416, 2008
Nóra Moldoványi, János Abonyi: Model Predictive Control of a Continuous Vacuum Crystalliser in an Industrial Environment, Chemical and Biochemical Engineering Quarterly, 2008
Varga Tamás, Szeifert Ferenc, Janos Abonyi: Decision tree and first-principles model based approach for reactor runaway analysis and forecasting, Engineering Applications of Artificial Intelligence, 2008
Dobos, Laszlo & Balasko, Balázs & Németh, Sándor & Abonyi, János: Energy resource and saving at operating plants based on historical process data, Eminent Conference, Veszprém, Hungary, 2008
Abonyi János: Adatbányászat, a hatékonyság eszköze, ComputerBooks kiadó, 2006
J. Abonyi and B. Feil: Cluster Analysis for Data Mining and System Identification, Birkhäuser, 2007
B. Balasko, J. Madar and J. Abonyi: Additive Sequential Evolutionary Design of Experiments, Lecture Notes in Artificial Intelligence, 2006
Abonyi, Janos & Feil, Balazs: Aggregation and Visualization of Fuzzy Clusters based on Fuzzy Similarity Measures, Advances in Fuzzy Clustering and its Applications, 2007
Balaskó Balázs, Németh Sándor, Abonyi János: Time-Series Similarity – Application to Qualitative Process Trend Analysis, Acta Agraria Kaposvariensis ( 6. Alkalmazott Informatika Konferencia, Kaposvár alapján), 2007
Tamas Kenesei , Johannes A. Roubos and Janos Abonyi: A Combination-of-Tools Method for Learning Interpretable Fuzzy Rule-Based Classifiers from Support Vector Machines, Lecture Notes in Computer Science series, Intelligent Data Engineering and Automated Learning - IDEAL 2007, 477-486, 2007
Agnes, Vathy-Fogarassy&Agnes, Werner-Stark&Janos, Abonyi: Topology Representing Networks for the Visualization of Manifolds, Journal of Mathematical Modelling and Algorithms, 2008
Balasko, B. & Nemeth, S. & Nagy, G. & Abonyi, J.: Integrated Process and Control System Model for Product Quality Control – Application to a Polypropylene Plant, Chemical Product and Process Modeling, 2008
Lakatos Béla: Generalized Coalescence/Redispersion Model for Micromixingin Chemical Reactors, Journal of Chemical Engineering of Japan, JCEJ Special Issue for ISCRE20, 2008
Pach F.P., Gyenesei A., Abonyi J.: MOSSFARM: Model Structure Selection by Fuzzy Association Rule Mining, Journal of Intelligent and Fuzzy Systems, Volume 19, Number 6 / 2008, Pages 399-407, 2008



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