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Yrjö Hiltunen

Yrjö Hiltunen

Research Director

Department of Technical Physics, Faculty of Science, Forestry and Technology

yrjo.hiltunen@uef.fi

Information Publications

Research groups

Process Informatics research group 15.05.2004 -

Publications

73/73 items

Combining Deep Learning Model and Evolutionary Optimization for Parameters Identification of NMR Signal
Ryzhikov, Ivan; Nikolskaya, Ekaterina; Hiltunen, Yrjö. Teoksessa: De Marsico, Maria; Sanniti di Baja, Gabriella; Fred, Ana(toim.) , 2022. Proceedings of the 11th International Conference on Pattern Recognition Applications and Methods (ICPRAM 2022) - Volume 1. s. 761-768. SCITEPRESS Science And Technology Publications
Risk estimation in data-driven fault prediction for a biomass-fired power plant
Ryzhikov, I; Liukkonen, M; Kettunen, A; Hiltunen, Y. Teoksessa: Merelo; Juan Julian; Garibaldi, Jonathan; Wagner,Christian; Bäck, Thomas; Madani, Kurosh; Warwick, Kevin(toim.) , 2021. Proceedings of the 12th International Joint Conference on Computational Intelligence. s. 423-429. SCITEPRESS Science And Technology Publications
MRI-kuvantaminen teollisuussovelluksissa
Nikolskaya, Ekaterina; Liukkonen, Mika; Hiltunen, Yrjö. Teoksessa: Soininen, Hanne; Pulkkinen, Lasse(toim.) , 2018. Metsä, ympäristö ja energia : Soveltavaa tutkimusta ja tuotekehitystä. Vuosijulkaisu 2017. s. 302-306. Kaakkois-Suomen ammattikorkeakoulu
Recognition of Systematic Spatial Patterns in Silicon Wafers Based on SOM and K-means
Liukkonen, Mika; Hiltunen, Yrjö. Teoksessa: (toim.) , 2018. . s. 439-444. International Federation of Automatic Control (IFAC)
Toward better control of water-intensive processes: Case study in fluting manufacturing
Liukkonen, Mika; Silvennoinen, Jukka; Hiltunen, Yrjö. Teoksessa: (toim.) , 2018. . s. 683-688. International Federation of Automatic Control (IFAC)
Fotoniikkasensori- ja korkean teknologian kuvantamisen demonstrointi metsäbiojalostamon hallintaan (Fokudemo-hanke)
Havia Elina, Käyhkö Jari, Hiltunen Yrjö, Kopra Riku, Liukkonen Mika. Teoksessa: Soininen Hanne, Pulkkinen Lasse(toim.) , 2017. Metsä, ympäristö ja energia : Soveltavaa tutkimusta ja tuotekehitystä. Vuosijulkaisu 2017. s. 272-279. Kaakkois-Suomen ammattikorkeakoulu
Teollisuusprosessien tehokkaammat tiedonjalostusratkaisut
Liukkonen Mika, Hiltunen Yrjö. Teoksessa: Soininen Hanne, Pulkkinen Lasse(toim.) , 2017. Metsä, ympäristö ja energia : Soveltavaa tutkimusta ja tuotekehitystä. Vuosijulkaisu 2017. s. 307-314. Kaakkois-Suomen ammattikorkeakoulu
A non-fouling online method for monitoring precipitation of metal ions in mine waters
Nikolskaya Ekaterina, Liukkonen Mika, Kankkunen Janne, Hiltunen Yrjö. 2015. IFAC proceedings volumes. 48: 98-101
A novel online method for monitoring precipitation of metals in mining waters
Nikolskaya Ekaterina, Liukkonen Mika, Kankkunen Janne, Hiltunen Yrjö. Teoksessa: Jämsä-Jounela Sirkka-Liisa(toim.) , 2015. Proceedings of Automaatio XXI. s. -.
Evaluation of Fluidized Bed Condition by Image Analysis and Modelling
Liukkonen Mika, Hiltunen Teri, Hiltunen Yrjö. 2015. IFAC proceedings volumes. 48: 892-897
Monitoring of water processes using intelligent condition indicators
Liukkonen Mika, Hiltunen Yrjö, Laakso Ilkka, Juntunen Petri. Teoksessa: Breitenecker Felix, Kugi Andreas, Troch Inge (eds.)(toim.) , 2015. Proceedings of the 8th Vienna International Conferenceon Mathematical Modelling MATHMOD 2015. s. 900-901.
Characterization of Alum Floc in Water Treatment by Image Analysis and Modeling
Juntunen P, Liukkonen M, Lehtola M, Hiltunen Y. 2014. Cogent engineering. 1: 944767
Life-cycle covering traceability and information management for electronic product using RFID
Liukkonen M, Havia E, Montonen H, Hiltunen Y. 2014. Tutkimuksia ja raportteja - Mikkelin ammattikorkeakoulu. A. . Mikkelin ammattikorkeakoulu
A new function for magnetic shape memory alloy Ni-Mn-Ga: Shrinkages formed from local magnetic fields
Ullakko Kari, Smith Aaron, Liukkonen Mika, Hiltunen Yrjö. 2013.
Adaptive Soft Sensor for Fluidized Bed Quality: Applications to Combustion of Biomass
Liukkonen M, Hälikkä E, Hiltunen T, Hiltunen Y. 2013. Fuel processing technology. 105: 46-51
Advanced monitoring and diagnosis of industrial processes
Liukkonen Mika, Hiltunen Yrjö, Laakso Ilkka. Teoksessa: Al-Begain K., Al-Dabass D., Orsoni A., Cant R., Zobel R.(toim.) , 2013. Proceedings of the 8th EUROSIM Congress on Modelling and Simulation. s. 112-117.
Advanced monitoring platform for industrial wastewater treatment: Multivariable approach using the self-organizing map
Liukkonen M, Laakso I, Hiltunen Y. 2013. Environmental modelling and software. 48: 193-201
Cluster analysis by self-organizing maps: An application to the modelling of water quality in a treatment process
Juntunen P, Liukkonen M, Lehtola M, Hiltunen Y. 2013. Applied soft computing. 13: 3191-3196
Dynamic Soft Sensors for Detecting Factors Affecting Turbidity in Drinking Water
Juntunen P., Liukkonen M, Lehtola M, Hiltunen Y. 2013. Journal of hydroinformatics. 15: 416-426
Monitoring of Air Emissions Using a Multivariable Model and Process History
Liukkonen Mika, Hiltunen Yrjö, Hiltunen Teri. Teoksessa: Al-Begain K., Al-Dabass D., Orsoni A., Cant R., Zobel R.(toim.) , 2013. Proceedings of the 8th EUROSIM Congress on Modelling and Simulation. s. 496-501.
A software platform for process monitoring: Applications to water treatment
Liukkonen M, Juntunen P, Laakso I, Hiltunen Y. 2012. Expert systems with applications. 40: 2631-2639
Characterization of Alum Floc by Image Analysis in Water Treatment Processes
Juntunen P, Liukkonen M, Lehtola M, Hiltunen Y. Teoksessa: Troch I, Breitenecker F(toim.) , 2012. Preprints Mathmod 2012 Vienna - 7th Vienna Conference on Mathematical Modelling. s. No. 325.
Characterization of Alum Floc in Water Treatment by Image Analysis
Juntunen Petri, Liukkonen Mika, Lehtola Markku, Hiltunen Yrjö. Teoksessa: Troch Inge, Breitenecker Felix(toim.) , 2012. Proceedings of Mathmod 2012 - 7th Vienna International Conference on Mathematical Modelling. s. 959-963. International Federation of Automatic Control
Computational Intelligence in Mass Soldering of Electronics - A Survey
Liukkonen M, Havia E, Hiltunen Y. 2012. Expert systems with applications. 39: 9928-9937
Dynamic Soft Sensors for NOx Emissions in a Circulating Fluidized Bed Boiler
Liukkonen M, Hälikkä E, Hiltunen T, Hiltunen Y.. Teoksessa: (toim.) , 2012. . s. 483¿490. Elsevier
Dynamic soft sensors for NOx emissions in a circulating fluidized bed boiler
Liukkonen M, Hälikkä E, Hiltunen T, Hiltunen Y. 2012. Applied energy. 97: 483-490
Low-cost Camera System for Online Estimation of Grain Size in Fluidized Bed
Liukkonen M, Huhtinen J, Hiltunen T, Hälikkä E, Hiltunen Y. Teoksessa: Troch I, Breitenecker F(toim.) , 2012. Preprints Mathmod 2012 Vienna - 7th Vienna Conference on Mathematical Modelling. s. No. 403.
Low-cost Online System for Detecting Unburned Fuel in a Large Industrial Biomass-fired Boiler
Liukkonen M, Huhtinen J, Hälikkä E, Hiltunen T, Hiltunen Y. Teoksessa: Perez Donsion M, Lopez Aguera A(toim.) , 2012. ICREPQ'12 - International Conference on Renewable Energies and Power Quality. s. N/A.
Low-cost camera system for online estimation of grain size in fluidized bed
Liukkonen Mika, Huhtinen Jouni, Hiltunen Teri, Hälikkä Eero, Hiltunen Yrjö. 2012.
Modeling of Water Quality: An Application to a Water Treatment Process
Juntunen P, Liukkonen M, Pelo M, Lehtola M, Hiltunen Y. 2012. Applied computational intelligence and soft computing. 2012: Article ID 846321
Artificial Neural Networks for Analysis of Process States in Fluidized Bed Combustion
Liukkonen M, Heikkinen M, Hiltunen T, Hälikkä E, Kuivalainen R, Hiltunen Y. 2011. Energy. 36: 339-347
Cluster Analysis of a Water Treatment Process by Self-Organizing Maps
Juntunen P., Liukkonen M., Lehtola M., Hiltunen Y.. Teoksessa: Ayesa E., Rodríquez-Roda I.(toim.) , 2011. Proceedings of the 8th IWA Symposium on Systems Analysis and Integrated Assessment, WATERMATEX 2011. s. 553-558.
Dynamic Modelling Approach for Detecting Turbidity in Drinking Water
Juntunen P, Liukkonen M, Lehtola MJ, Hiltunen Y. Teoksessa: Dahlquist E(toim.) , 2011. Proceedings of the 52nd International Conference of Scandinavian Simulation Society. s. paper 19.
Dynamic simulation of a full scale WWTP digestion process for energy efficiency improvement
Poutiainen H, Juntunen P, Heinonen-Tanski H, Hiltunen Y. 2011.
Expert system for analysis of quality in production of electronics
Liukkonen Mika, Havia Elina, Leinonen Hannu, Hiltunen Yrjö. 2011. Expert systems with applications. 38: 8724-8729
Modeling Software for Advanced Industrial Diagnostics
Liukkonen M, Heikkinen M, Hiltunen T, Kapanen J, Hiltunen Y. Teoksessa: Dahlquist E(toim.) , 2011. Proceedings of the 52nd International Conference of Scandinavian Simulation Society. s. paper 5.
Modeling of the Fluidized Bed Combustion Process and NOx Emissions Using Self-Organizing Maps: An Application to the Diagnosis of Process States
Liukkonen M, Hiltunen T, Hälikkä E, Hiltunen Y. 2011. Environmental modelling and software. 26: 605-614
Subtraction analysis based on self-organizing maps for an industrial wastewater treatment process
Heikkinen Mikko, Poutiainen Hannu, Liukkonen Mika, Heikkinen Tomi, Hiltunen Yrjö. 2011. Mathematics and computers in simulation. 82: 450-459
Water Contents of Wood and Peat Based Fuels by Analyzing Time Domain NMR data
Nikolskaya E, Liukkonen M, Kauppinen RA, Grunin L, Hiltunen Y. Teoksessa: Dahlquist E(toim.) , 2011. Proceedings of the 52nd International Conference of Scandinavian Simulation Society. s. paper 6.
Adaptive Soft Sensor for Fluidized Bed Quality
Liukkonen M, Hälikkä E, Hiltunen T & Hiltunen Y. Teoksessa: -(toim.) , 2010. Impacts of Fuel Quality on Power Production & Environment Conference. s. Article #19.
Analysis of flue gas emission data from fluidized bed combustion using self-organizing maps
Liukkonen M, Heikkinen M, Hälikkä E, Hiltunen T & Hiltunen Y. 2010. Applied computational intelligence and soft computing. 2010: 8 p.
Correlating tissue outcome with quantitative multiparametric MRI of acute cerebral ischemia in rats
Jokivarsi KT, Hiltunen Y, Tuunanen PI, Kauppinen RA & Gröhn OH. 2010. Journal of cerebral blood flow and metabolism. 30: 415-427
Estimation of the onset time of cerebral ischemia using T1rho and T2 MRI in rats
Jokivarsi KT, Hiltunen Y, Gröhn H, Tuunanen P, Gröhn OH & Kauppinen RA. 2010. Stroke. 41: 2335-2340
Modeling of nitrogen oxide emissions in fluidized bed combustion using artificial neural networks
Liukkonen M, Hälikkä E, Kuivalainen R & Hiltunen Y. 2010. International Journal of Data Engineering. 1: 26-35
Modelling of Residual Aluminum in Water Treatment Process
Juntunen P, Liukkonen M, Pelo M, Lehtola M & Hiltunen Y. Teoksessa: Snorek M, Buk Z, Cepek M & Drchal J (eds.)(toim.) , 2010. Proceedings of the 7th EUROSIM Congress on Modelling and Simulation. s. Article #249.
Modelling of Turbidity in Water Treatment Process
Juntunen P, Liukkonen M, Pelo M, Lehtola M, Hiltunen Y. Teoksessa: Juuso E(toim.) , 2010. Proceedings of the 51st Conference on Simulation and Modelling. s. F_6060.
Quality-oriented optimization of wave soldering process by using self-organizing maps
Liukkonen M, Havia E, Leinonen H & Hiltunen Y. 2010. Applied soft computing. 11: 214-220
A modelling and optimization system for fluidized bed power plants
Heikkinen M, Hiltunen T, Liukkonen M, Kettunen A, Kuivalainen R, Hiltunen Y. 2009. Expert systems with applications. 36: 10274-10279
Application of self-organizing maps in analysis of wave soldering process
Liukkonen M, Havia E, Leinonen H, Hiltunen Y. 2009. Expert systems with applications. 36: 4604-4609
Emission analysis of a fluidized bed boiler by using self-organizing maps
Liukkonen M, Heikkinen M, Hälikkä E, Kuivalainen R, Hiltunen Y. Teoksessa: Kolehmainen M, Toivanen P, Beliczynki B(toim.) , 2009. Adaptive and Natural Computing Algrorithms - 9th International Conference, ICANNGA. s. 119-129.
Estimation of VLDL, IDL, LDL, HDL2, apoA-I, and apoB from the Friedewald inputs-apoB and IDL, but not LDL, are associated with mortality in type 1 diabetes
Niemi J, Mäkinen V-P, Heikkonen J, Tenkanen L, Hiltunen Y, Hannuksela ML, Jauhiainen M, Forsblom C, Taskinen M-R, Kesäniemi YA, Savolainen MJ, Kaski K, Groop P-H, Kovanen PT, Ala-Korpela M. 2009. Annals of medicine. 41: 451-461
Modeling of process states by using artificial neural networks in a fluidized bed energy plant
Liukkonen M, Heikkinen M, Hiltunen T, Hälikkä E, Kuivalainen R, Hiltunen Y. Teoksessa: Troch I, Breitenecker F(toim.) , 2009. MATHMOD - 6th Vienna Conference on Mathematical Modelling. s. 397-402.
Modeling of soldering quality by using artificial neural networks
Liukkonen M, Hiltunen T, Havia E, Leinonen H, Hiltunen Y. 2009. IEEE transactions on electronics packaging manufacturing. 32: 89-96
Process state identification and modeling in a fluidized bed energy plant by using artificial neural networks
Liukkonen M, Hälikkä E, Kuivalainen R, Hiltunen Y. Teoksessa: (toim.) , 2009. Finnish-Swedish Flame Days 2009. s. . The Finnish and Swedish National Committees of IFRF
SOM-based subtraction analysis to process data of an activated sludge treatment plant
Heikkinen M, Poutiainen H, Liukkonen M, Heikkinen T, Hiltunen Y. Teoksessa: Troch I, Breitenecker F(toim.) , 2009. MATHMOD - 6th Vienna Conference on Mathematical Modelling. s. 1021-1026.
Self-organizing maps for analysis of process emissions in fluidized bed energy plant
Liukkonen M, Heikkinen M, Hiltunen Y, Hälikkä E, Hiltunen T. Teoksessa: Elmegaard B, Veje C, Nielsen MP, Molbak T(toim.) , 2009. Proceedings of SIMS 50 - the 50th International Conference of Scandinavian Simulation Society. s. 237-243.
A modeling and optimization tool for the expandable polystyrene batch process
Heikkinen M, Nurminen V, Hiltunen T, Hiltunen Y. 2008. Chemical product and process modeling. 3: Article 1
Modelling of activated sludge treatment process in a pulp mill using neutral networks
Heikkinen M, Heikkinen T, Hiltunen Y. Teoksessa: Zinn CD, Chu H-W, Savoie M, Ferrer J, Munitic A(toim.) , 2008. International Multi-Conference on Engineering and Technological Innovation. s. 333-337. IIIS
Neural networks in process life cycle profit modelling
Räsänen T, Soukka R, Kokki S, Hiltunen Y. 2008. Expert systems with applications. 35: 604-610
Process states and their submodels using self-organizing maps in an activated sludge treatment plant
Heikkinen M, Heikkinen T, Hiltunen Y. Teoksessa: (toim.) , 2008. Proceedings of SIMS 2008: The 48th Scandinavian Conference on Simulation and Modelling [CD ROM]. s. 2 s. NFA. Oslo University College, Faculty of Engineering
SOM-based modelling for an sctivated sludge treatment process
Heikkinen M, Latvala T, Juuso E, Hiltunen Y. Teoksessa: Al-Dabass D, Orsoni A, Brentnall A, Abraham A, Zober R(toim.) , 2008. EUROSIM/UKSim2008. Tenth International Conference on Computer Modelling and Simulation [CD ROM]. s. 224-229. IEEE
Selecting variables for quality predictions in wave soldering by using multi-layer perceptrons
Liukkonen M, Hiltunen T, Havia E, Leinonen H, Hiltunen Y. Teoksessa: Tuominen A, Kantola J, Suominen A, Hyrynsalmi S(toim.) , 2008. Proceedings of NEXT 2008. The Fifth International New Exploratory Technologies Conference. s. 373-382. Turku Centre for Computer Science
A modeling and optimization tool for the expandable polystyrene batch process
Heikkinen M, Nurminen V, Hiltunen T, Hiltunen Y. Teoksessa: Jämsä-Jounela S-L(toim.) , 2007. 14th Nordic Process Control Workshop. s. 159-163. Helsinki University
A som-based approach for analysing and modelling a wave soldering process
Liukkonen M, Havia E, Leinonen H, Hiltunen Y. Teoksessa: Jämsä-Jounela S-L(toim.) , 2007. 14th Nordic process control workshop. s. 126-129. Helsinki University of Technology
Application of Self-Organizing Maps in Analysis of Wave Soldering Process
Liukkonen Mika, Havia Elina, Leinonen Hannu, Hiltunen Yrjö. Teoksessa: Zupancic B., Karba R., Blazic S.(toim.) , 2007. Proceedings of the 6th EUROSIM Congress on Modelling and Simulation. s. paper 430.
Independent component analysis to mass spectra of aluminium sulphate
Heikkinen M, Sarpola A, Hellman H, Rämö J, Hiltunen Y. 2007. INTERNATIONAL JOURNAL OF APPLIED MATHEMATICS AND COMPUTER SCIENCES. 4: 675-679
A som-based tool for process state monitoring and optimization
Hiltunen Y, Heikkinen M, Hiltunen T, Räsänen T, Huhtinen J, Kettunen A. Teoksessa: Juuso E(toim.) , 2006. SIMS 2006 Proceedings of The 47th Conference on Simulation and Modelling. s. 164-169. Finnish Society of Automation and SIMS
Data-based approaches improving the accuracy of life cycle profit models
Räsänen T, Soukka R, Kokki S, Hiltunen T, Heikkinen M, Kuivalainen R, Hiltunen Y. Teoksessa: (toim.) , 2006. ALSIS '06 Ist IFAC Workshop on Applications of Large Scale Industrial Systems. s. . IFAC, FSA
Neural network based method for analysis of eps-batch process
Heikkinen M, Nurminen V, Hiltunen Y. Teoksessa: Juuso E(toim.) , 2006. SIMS 2006 Proceedings of The 47th Conference on Simulation and Modelling. s. 288-91. Finnish Society for Automation and SIMS
Self-organizing maps for analysis of EPS-batch process
Heikkinen M, Nurminen V, Hiltunen Y. Teoksessa: (toim.) , 2006. ALSIS '06 Ist IFAC Workshop on Applications of Large Scale Industrial Systems. s. . IFAC, FSA
Self-refreshing SOM for dynamic process state monitoring in a circulating fluidized bed energy plant
Räsänen T, Kettunen A, Niemitalo E, Hiltunen Y. Teoksessa: (toim.) , 2006. IS06 2006 3rd International IEEE Conference Intelligent Systems". s. 344-349. IEEE IM/SMC and Harrow School of Computer Science
Application of self-organizing maps for process state monitoring and optimization
Heikkinen M, Kettunen A, Niemitalo E, Kuivalainen R, Hiltunen Y. Teoksessa: Lecoeuche S, Tsaptsinos D(toim.) , 2005. Novel Applications of Neural Networks in Engineering. Proceedings of the Ninth International Conference on Engineering Applications of Neural Nerworks. s. 79-83. Ecole des Mines de Douai
SOM-Based method for process state monitoring and optimization in fluidized bed energy plant
Heikkinen M, Kettunen A, Niemitalo E, Kuivalainen R, Hiltunen Y. Teoksessa: Duch W, Kacprzyk J, Oja E, Zadrozny S(toim.) , 2005. Artificial Neural networks: Biological Inspirations - ICANN 2005. 15th International Conference. Proceedings, Part I. s. 409-414. Springer

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Yrjö Hiltunen

Research groups

Combining Deep Learning Model and Evolutionary Optimization for Parameters Identification of NMR Signal

Risk estimation in data-driven fault prediction for a biomass-fired power plant

MRI-kuvantaminen teollisuussovelluksissa

Recognition of Systematic Spatial Patterns in Silicon Wafers Based on SOM and K-means

Toward better control of water-intensive processes: Case study in fluting manufacturing

Fotoniikkasensori- ja korkean teknologian kuvantamisen demonstrointi metsäbiojalostamon hallintaan (Fokudemo-hanke)

Teollisuusprosessien tehokkaammat tiedonjalostusratkaisut

A non-fouling online method for monitoring precipitation of metal ions in mine waters

A novel online method for monitoring precipitation of metals in mining waters

Evaluation of Fluidized Bed Condition by Image Analysis and Modelling

Monitoring of water processes using intelligent condition indicators

Characterization of Alum Floc in Water Treatment by Image Analysis and Modeling

Life-cycle covering traceability and information management for electronic product using RFID

A new function for magnetic shape memory alloy Ni-Mn-Ga: Shrinkages formed from local magnetic fields

Adaptive Soft Sensor for Fluidized Bed Quality: Applications to Combustion of Biomass

Advanced monitoring and diagnosis of industrial processes

Advanced monitoring platform for industrial wastewater treatment: Multivariable approach using the self-organizing map

Cluster analysis by self-organizing maps: An application to the modelling of water quality in a treatment process

Dynamic Soft Sensors for Detecting Factors Affecting Turbidity in Drinking Water

Monitoring of Air Emissions Using a Multivariable Model and Process History

A software platform for process monitoring: Applications to water treatment

Characterization of Alum Floc by Image Analysis in Water Treatment Processes

Characterization of Alum Floc in Water Treatment by Image Analysis

Computational Intelligence in Mass Soldering of Electronics - A Survey

Dynamic Soft Sensors for NOx Emissions in a Circulating Fluidized Bed Boiler

Dynamic soft sensors for NOx emissions in a circulating fluidized bed boiler

Low-cost Camera System for Online Estimation of Grain Size in Fluidized Bed

Low-cost Online System for Detecting Unburned Fuel in a Large Industrial Biomass-fired Boiler

Low-cost camera system for online estimation of grain size in fluidized bed

Modeling of Water Quality: An Application to a Water Treatment Process

Artificial Neural Networks for Analysis of Process States in Fluidized Bed Combustion

Cluster Analysis of a Water Treatment Process by Self-Organizing Maps

Dynamic Modelling Approach for Detecting Turbidity in Drinking Water

Dynamic simulation of a full scale WWTP digestion process for energy efficiency improvement

Expert system for analysis of quality in production of electronics

Modeling Software for Advanced Industrial Diagnostics

Modeling of the Fluidized Bed Combustion Process and NOx Emissions Using Self-Organizing Maps: An Application to the Diagnosis of Process States

Subtraction analysis based on self-organizing maps for an industrial wastewater treatment process

Water Contents of Wood and Peat Based Fuels by Analyzing Time Domain NMR data

Adaptive Soft Sensor for Fluidized Bed Quality

Analysis of flue gas emission data from fluidized bed combustion using self-organizing maps

Correlating tissue outcome with quantitative multiparametric MRI of acute cerebral ischemia in rats

Estimation of the onset time of cerebral ischemia using T1rho and T2 MRI in rats

Modeling of nitrogen oxide emissions in fluidized bed combustion using artificial neural networks

Modelling of Residual Aluminum in Water Treatment Process

Modelling of Turbidity in Water Treatment Process

Quality-oriented optimization of wave soldering process by using self-organizing maps

A modelling and optimization system for fluidized bed power plants

Application of self-organizing maps in analysis of wave soldering process

Emission analysis of a fluidized bed boiler by using self-organizing maps

Estimation of VLDL, IDL, LDL, HDL2, apoA-I, and apoB from the Friedewald inputs-apoB and IDL, but not LDL, are associated with mortality in type 1 diabetes

Modeling of process states by using artificial neural networks in a fluidized bed energy plant

Modeling of soldering quality by using artificial neural networks

Process state identification and modeling in a fluidized bed energy plant by using artificial neural networks

SOM-based subtraction analysis to process data of an activated sludge treatment plant

Self-organizing maps for analysis of process emissions in fluidized bed energy plant

A modeling and optimization tool for the expandable polystyrene batch process

Modelling of activated sludge treatment process in a pulp mill using neutral networks

Neural networks in process life cycle profit modelling

Process states and their submodels using self-organizing maps in an activated sludge treatment plant

SOM-based modelling for an sctivated sludge treatment process

Selecting variables for quality predictions in wave soldering by using multi-layer perceptrons

A modeling and optimization tool for the expandable polystyrene batch process

A som-based approach for analysing and modelling a wave soldering process

Application of Self-Organizing Maps in Analysis of Wave Soldering Process

Independent component analysis to mass spectra of aluminium sulphate

A som-based tool for process state monitoring and optimization

Data-based approaches improving the accuracy of life cycle profit models

Neural network based method for analysis of eps-batch process

Self-organizing maps for analysis of EPS-batch process

Self-refreshing SOM for dynamic process state monitoring in a circulating fluidized bed energy plant

Application of self-organizing maps for process state monitoring and optimization

SOM-Based method for process state monitoring and optimization in fluidized bed energy plant