YRJö HILTUNEN

Contact info

Research groups - UEF

• 
  Process Informatics research group

PROJECTS - UEF

• 
  ENERVE - Energy-efficient dewatering

Publications

• Risk estimation in data-driven fault prediction for a biomass-fired power plant. Ryzhikov, I; Liukkonen, M; Kettunen, A; Hiltunen, Y / Proceedings of the 12th International Joint Conference on Computational Intelligence. 2021. 2021
• Recognition of Systematic Spatial Patterns in Silicon Wafers Based on SOM and K-means. Liukkonen, Mika; Hiltunen, Yrjö. IFAC proceedings volumes. 2018. 2018
• Toward better control of water-intensive processes: Case study in fluting manufacturing. Liukkonen, Mika; Silvennoinen, Jukka; Hiltunen, Yrjö. IFAC proceedings volumes. 2018. 2018
• Nikolskaya, Ekaterina; Liukkonen, Mika; Hiltunen, Yrjö. 2018. MRI-kuvantaminen teollisuussovelluksissa. In: Soininen, Hanne; Pulkkinen, Lasse (ed.) Metsä, ympäristö ja energia : Soveltavaa tutkimusta ja tuotekehitystä. Vuosijulkaisu 2017. Kaakkois-Suomen ammattikorkeakoulu. Xamk Kehittää 28. s. 302-306. 2018
• Havia Elina, Käyhkö Jari, Hiltunen Yrjö, Kopra Riku, Liukkonen Mika. 2017. Fotoniikkasensori- ja korkean teknologian kuvantamisen demonstrointi metsäbiojalostamon hallintaan (Fokudemo-hanke). In: Soininen Hanne, Pulkkinen Lasse (ed.) Metsä, ympäristö ja energia : Soveltavaa tutkimusta ja tuotekehitystä. Vuosijulkaisu 2017. Kaakkois-Suomen ammattikorkeakoulu. Xamk Kehittää 28. s. 272-279. 2017
• Liukkonen Mika, Hiltunen Yrjö. 2017. Teollisuusprosessien tehokkaammat tiedonjalostusratkaisut. In: Soininen Hanne, Pulkkinen Lasse (ed.) Metsä, ympäristö ja energia : Soveltavaa tutkimusta ja tuotekehitystä. Vuosijulkaisu 2017. Kaakkois-Suomen ammattikorkeakoulu. Xamk Kehittää 28. s. 307-314. 2017
• Liukkonen Mika, Hiltunen Teri, Hiltunen Yrjö. 2015. Evaluation of Fluidized Bed Condition by Image Analysis and Modelling. IFAC Proceedings Volumes 48 1: 892-897. 2015
• Liukkonen Mika, Hiltunen Yrjö, Laakso Ilkka, Juntunen Petri. 2015. Monitoring of water processes using intelligent condition indicators. In: Breitenecker Felix, Kugi Andreas, Troch Inge (eds.) (ed.) , Proceedings of the 8th Vienna International Conferenceon Mathematical Modelling MATHMOD 2015. IFAC-PapersOnLine volume 48, issue 1. s. 900-901. 2015
• Nikolskaya Ekaterina, Liukkonen Mika, Kankkunen Janne, Hiltunen Yrjö. 2015. A non-fouling online method for monitoring precipitation of metal ions in mine waters. IFAC Proceedings Volumes 48 17: 98-101. 2015
• Nikolskaya Ekaterina, Liukkonen Mika, Kankkunen Janne, Hiltunen Yrjö. 2015. A novel online method for monitoring precipitation of metals in mining waters. In: Jämsä-Jounela Sirkka-Liisa (ed.) , Proceedings of Automaatio XXI. SAS julkaisusarja 44. s. -. 2015
• Juntunen P, Liukkonen M, Lehtola M, Hiltunen Y. 2014. Characterization of Alum Floc in Water Treatment by Image Analysis and Modeling. Cogent Engineering 1 1: 944767. 2014
• Life-cycle covering traceability and information management for electronic product using RFID. Liukkonen M, Havia E, Montonen H, Hiltunen Y. 2014 2014
• Liukkonen Mika, Hiltunen Yrjö, Laakso Ilkka. 2013. Advanced monitoring and diagnosis of industrial processes: Al-Begain K., Al-Dabass D., Orsoni A., Cant R., Zobel R., Proceedings of the 8th EUROSIM Congress on Modelling and Simulation. 112-117. 2013
• Ullakko Kari, Smith Aaron, Liukkonen Mika, Hiltunen Yrjö. 2013. A new function for magnetic shape memory alloy Ni-Mn-Ga: Shrinkages formed from local magnetic fields, Proceedings of the International Conference on Functional Materials. N/A. 2013
• Liukkonen Mika, Hiltunen Yrjö, Hiltunen Teri. 2013. Monitoring of Air Emissions Using a Multivariable Model and Process History: Al-Begain K., Al-Dabass D., Orsoni A., Cant R., Zobel R., Proceedings of the 8th EUROSIM Congress on Modelling and Simulation. 496-501. 2013
• Liukkonen M, Laakso I, Hiltunen Y. 2013. Advanced monitoring platform for industrial wastewater treatment: Multivariable approach using the self-organizing map. ENVIRONMENTAL MODELLING & SOFTWARE 48: 193-201. 2013
• Liukkonen M, Hälikkä E, Hiltunen T, Hiltunen Y. 2013. Adaptive Soft Sensor for Fluidized Bed Quality: Applications to Combustion of Biomass. FUEL PROCESSING TECHNOLOGY 105: 46-51. 2013
• Juntunen P., Liukkonen M, Lehtola M, Hiltunen Y. 2013. Dynamic Soft Sensors for Detecting Factors Affecting Turbidity in Drinking Water. Journal of Hydroinformatics 15 2: 416-426. 2013
• Juntunen P, Liukkonen M, Lehtola M, Hiltunen Y. 2013. Cluster analysis by self-organizing maps: An application to the modelling of water quality in a treatment process. Applied Soft Computing 13 7: 3191-3196. 2013
• Liukkonen M, Hälikkä E, Hiltunen T, Hiltunen Y. 2012. Dynamic soft sensors for NOx emissions in a circulating fluidized bed boiler APPLIED ENERGY 97: 483-490. 2012
• Liukkonen Mika, Huhtinen Jouni, Hiltunen Teri, Hälikkä Eero, Hiltunen Yrjö. 2012. Low-cost camera system for online estimation of grain size in fluidized bed: Troch I., Breitenecker F., Proceedings of Mathmod 2012 ¿ 7th Vienna International Conference on Mathematical Modelling. 964-967. 2012
• Liukkonen M, Juntunen P, Laakso I, Hiltunen Y. 2012. A software platform for process monitoring: Applications to water treatment. EXPERT SYSTEMS WITH APPLICATIONS 40 7: 2631-2639. 2012
• Liukkonen M, Hälikkä E, Hiltunen T, Hiltunen Y.. 2012. Dynamic Soft Sensors for NOx Emissions in a Circulating Fluidized Bed Boiler.Elsevier. 483¿490. 2012
• Liukkonen M, Huhtinen J, Hiltunen T, Hälikkä E, Hiltunen Y. 2012. Low-cost Camera System for Online Estimation of Grain Size in Fluidized Bed: Troch I, Breitenecker F, Preprints Mathmod 2012 Vienna - 7th Vienna Conference on Mathematical Modelling. ARGESIM report AR-S38. No. 403. 2012
• Liukkonen M, Huhtinen J, Hälikkä E, Hiltunen T, Hiltunen Y. 2012. Low-cost Online System for Detecting Unburned Fuel in a Large Industrial Biomass-fired Boiler: Perez Donsion M, Lopez Aguera A, ICREPQ'12 - International Conference on Renewable Energies and Power Quality. N/A. 2012
• Liukkonen M, Havia E, Hiltunen Y. 2012. Computational Intelligence in Mass Soldering of Electronics - A Survey EXPERT SYSTEMS WITH APPLICATIONS 39 10: 9928-9937. 2012
• Juntunen Petri, Liukkonen Mika, Lehtola Markku, Hiltunen Yrjö. 2012. Characterization of Alum Floc in Water Treatment by Image Analysis: Troch Inge, Breitenecker Felix, Proceedings of Mathmod 2012 - 7th Vienna International Conference on Mathematical Modelling.International Federation of Automatic Control. Mathematical Modelling 7. 959-963. 2012
• Juntunen P, Liukkonen M, Pelo M, Lehtola M, Hiltunen Y. 2012. Modeling of Water Quality: An Application to a Water Treatment Process. Applied Computational Intelligence and Soft Computing 2012: Article ID 846321. 2012
• Juntunen P, Liukkonen M, Lehtola M, Hiltunen Y. 2012. Characterization of Alum Floc by Image Analysis in Water Treatment Processes: Troch I, Breitenecker F, Preprints Mathmod 2012 Vienna - 7th Vienna Conference on Mathematical Modelling. ARGESIM report AR-S38. No. 325. 2012
• Liukkonen M, Hiltunen T, Hälikkä E, Hiltunen Y. 2011. Modeling of the Fluidized Bed Combustion Process and NOx Emissions Using Self-Organizing Maps: An Application to the Diagnosis of Process States ENVIRONMENTAL MODELLING & SOFTWARE 26 5: 605-614. 2011
• Poutiainen H, Juntunen P, Heinonen-Tanski H, Hiltunen Y. 2011. Dynamic simulation of a full scale WWTP digestion process for energy efficiency improvement. In: (ed.) , The 12 th Nordic/NORDIWA Wastewater Conference, 14.-16. November 2011, Helsinki, Finland. ss. 17. 2011
• Liukkonen Mika, Havia Elina, Leinonen Hannu, Hiltunen Yrjö. 2011. Expert system for analysis of quality in production of electronics. EXPERT SYSTEMS WITH APPLICATIONS 38: 8724-8729. 2011
• Nikolskaya E, Liukkonen M, Kauppinen RA, Grunin L, Hiltunen Y. 2011. Water Contents of Wood and Peat Based Fuels by Analyzing Time Domain NMR data: Dahlquist E, Proceedings of the 52nd International Conference of Scandinavian Simulation Society. paper 6. 2011
• Liukkonen M, Heikkinen M, Hiltunen T, Kapanen J, Hiltunen Y. 2011. Modeling Software for Advanced Industrial Diagnostics: Dahlquist E, Proceedings of the 52nd International Conference of Scandinavian Simulation Society. paper 5. 2011
• Juntunen P., Liukkonen M., Lehtola M., Hiltunen Y.. 2011. Cluster Analysis of a Water Treatment Process by Self-Organizing Maps: Ayesa E., Rodríquez-Roda I., Proceedings of the 8th IWA Symposium on Systems Analysis and Integrated Assessment, WATERMATEX 2011. 553-558. 2011
• Juntunen P, Liukkonen M, Lehtola MJ, Hiltunen Y. 2011. Dynamic Modelling Approach for Detecting Turbidity in Drinking Water: Dahlquist E, Proceedings of the 52nd International Conference of Scandinavian Simulation Society. paper 19. 2011
• Heikkinen Mikko, Poutiainen Hannu, Liukkonen Mika, Heikkinen Tomi, Hiltunen Yrjö. 2011. Subtraction analysis based on self-organizing maps for an industrial wastewater treatment process MATHEMATICS AND COMPUTERS IN SIMULATION 82 3: 450-459. 2011
• Liukkonen M, Heikkinen M, Hiltunen T, Hälikkä E, Kuivalainen R, Hiltunen Y. 2011. Artificial Neural Networks for Analysis of Process States in Fluidized Bed Combustion. Energy 36 1: 339-347. 2011
• Jokivarsi KT, Hiltunen Y, Gröhn H, Tuunanen P, Gröhn OH & Kauppinen RA. 2010. Estimation of the onset time of cerebral ischemia using T1rho and T2 MRI in rats. STROKE 41: 2335-2340. 2010
• Jokivarsi KT, Hiltunen Y, Tuunanen PI, Kauppinen RA & Gröhn OH. 2010. Correlating tissue outcome with quantitative multiparametric MRI of acute cerebral ischemia in rats. JOURNAL OF CEREBRAL BLOOD FLOW AND METABOLISM 30: 415-427. 2010
• Juntunen P, Liukkonen M, Pelo M, Lehtola M & Hiltunen Y. 2010. Modelling of Residual Aluminum in Water Treatment Process. In: Snorek M, Buk Z, Cepek M & Drchal J (eds.) (ed.) , Proceedings of the 7th EUROSIM Congress on Modelling and Simulation. ss. Article #249. 2010
• Juntunen P, Liukkonen M, Pelo M, Lehtola M, Hiltunen Y. 2010. Modelling of Turbidity in Water Treatment Process. In: Juuso E (ed.) , Proceedings of the 51st Conference on Simulation and Modelling. ss. F_6060. 2010
• Liukkonen M, Havia E, Leinonen H & Hiltunen Y. 2010. Quality-oriented optimization of wave soldering process by using self-organizing maps. Applied Soft Computing 11 1: 214-220. 2010
• Liukkonen M, Heikkinen M, Hälikkä E, Hiltunen T & Hiltunen Y. 2010. Analysis of flue gas emission data from fluidized bed combustion using self-organizing maps. Applied Computational Intelligence and Soft Computing 2010 Article ID 932467: 8 p.. 2010
• Liukkonen M, Hälikkä E, Hiltunen T & Hiltunen Y. 2010. Adaptive Soft Sensor for Fluidized Bed Quality: -, Impacts of Fuel Quality on Power Production & Environment Conference. Article #19. 2010
• Liukkonen M, Hälikkä E, Kuivalainen R & Hiltunen Y. 2010. Modeling of nitrogen oxide emissions in fluidized bed combustion using artificial neural networks. International Journal of Data Engineering 1 2: 26-35. 2010
• Liukkonen M, Heikkinen M, Hälikkä E, Kuivalainen R, Hiltunen Y. 2009. Emission analysis of a fluidized bed boiler by using self-organizing maps: Kolehmainen M, Toivanen P, Beliczynki B, Adaptive and Natural Computing Algrorithms - 9th International Conference, ICANNGA. 119-129. 2009
• 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. 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. Annals of Medicine 41: 451-461. 2009
• Liukkonen M, Hälikkä E, Kuivalainen R, Hiltunen Y. 2009. Process state identification and modeling in a fluidized bed energy plant by using artificial neural networks. In: (ed.) , Finnish-Swedish Flame Days 2009.The Finnish and Swedish National Committees of IFRF. ss. 2009
• Liukkonen M, Hiltunen T, Havia E, Leinonen H, Hiltunen Y. 2009. Modeling of soldering quality by using artificial neural networks IEEE TRANSACTIONS ON ELECTRONICS PACKAGING MANUFACTURING 32 2: 89-96. 2009
• Liukkonen M, Heikkinen M, Hiltunen Y, Hälikkä E, Hiltunen T. 2009. Self-organizing maps for analysis of process emissions in fluidized bed energy plant: Elmegaard B, Veje C, Nielsen MP, Molbak T, Proceedings of SIMS 50 - the 50th International Conference of Scandinavian Simulation Society. 237-243. 2009
• Liukkonen M, Havia E, Leinonen H, Hiltunen Y. 2009. Application of self-organizing maps in analysis of wave soldering process. EXPERT SYSTEMS WITH APPLICATIONS 36: 4604-4609. 2009
• Heikkinen M, Poutiainen H, Liukkonen M, Heikkinen T, Hiltunen Y. 2009. SOM-based subtraction analysis to process data of an activated sludge treatment plant. In: Troch I, Breitenecker F (ed.) , MATHMOD - 6th Vienna Conference on Mathematical Modelling. ARGESIM report. ss. 1021-1026. 2009
• Heikkinen M, Hiltunen T, Liukkonen M, Kettunen A, Kuivalainen R, Hiltunen Y. 2009. A modelling and optimization system for fluidized bed power plants. EXPERT SYSTEMS WITH APPLICATIONS 36: 10274-10279. 2009
• Liukkonen M, Heikkinen M, Hiltunen T, Hälikkä E, Kuivalainen R, Hiltunen Y. 2009. Modeling of process states by using artificial neural networks in a fluidized bed energy plant: Troch I, Breitenecker F, MATHMOD - 6th Vienna Conference on Mathematical Modelling. ARGESIM report. 397-402. 2009
• Heikkinen M, Heikkinen T, Hiltunen Y. 2008. Modelling of activated sludge treatment process in a pulp mill using neutral networks: Zinn CD, Chu H-W, Savoie M, Ferrer J, Munitic A, International Multi-Conference on Engineering and Technological Innovation.IIIS. 333-337. 2008
• Heikkinen M, Heikkinen T, Hiltunen Y. 2008. Process states and their submodels using self-organizing maps in an activated sludge treatment plant, Proceedings of SIMS 2008: The 48th Scandinavian Conference on Simulation and Modelling [CD ROM].NFA. Oslo University College, Faculty of Engineering. 2 s. 2008
• Heikkinen M, Latvala T, Juuso E, Hiltunen Y. 2008. SOM-based modelling for an sctivated sludge treatment process: Al-Dabass D, Orsoni A, Brentnall A, Abraham A, Zober R, EUROSIM/UKSim2008. Tenth International Conference on Computer Modelling and Simulation [CD ROM].IEEE. 224-229. 2008
• Heikkinen M, Nurminen V, Hiltunen T, Hiltunen Y. 2008. A modeling and optimization tool for the expandable polystyrene batch process. CHEMICAL PRODUCT AND PROCESS MODELING 3 1: Article 1. 2008
• Liukkonen M, Hiltunen T, Havia E, Leinonen H, Hiltunen Y. 2008. Selecting variables for quality predictions in wave soldering by using multi-layer perceptrons: Tuominen A, Kantola J, Suominen A, Hyrynsalmi S, Proceedings of NEXT 2008. The Fifth International New Exploratory Technologies Conference.Turku Centre for Computer Science. TUCS General Publication. 373-382. 2008
• Räsänen T, Soukka R, Kokki S, Hiltunen Y. 2008. Neural networks in process life cycle profit modelling. EXPERT SYSTEMS WITH APPLICATIONS 35: 604-610. 2008
• Liukkonen Mika, Havia Elina, Leinonen Hannu, Hiltunen Yrjö. 2007. Application of Self-Organizing Maps in Analysis of Wave Soldering Process. In: Zupancic B., Karba R., Blazic S. (ed.) , Proceedings of the 6th EUROSIM Congress on Modelling and Simulation. ss. paper 430. 2007
• Heikkinen M, Nurminen V, Hiltunen T, Hiltunen Y. 2007. A modeling and optimization tool for the expandable polystyrene batch process: Jämsä-Jounela S-L, 14th Nordic Process Control Workshop.Helsinki University. Helsinki University of Technology. Laboratory of Process Control and Automation. 159-163. 2007
• Liukkonen M, Havia E, Leinonen H, Hiltunen Y. 2007. A som-based approach for analysing and modelling a wave soldering process: Jämsä-Jounela S-L, 14th Nordic process control workshop.Helsinki University of Technology. Report / Helsinki University of Technology. Laboratory of Process Control and Automation. 126-129. 2007
• Heikkinen M, Sarpola A, Hellman H, Rämö J, Hiltunen Y. 2007. Independent component analysis to mass spectra of aluminium sulphate. INTERNATIONAL JOURNAL OF APPLIED MATHEMATICS AND COMPUTER SCIENCES 4 2: 675-679. 2007
• Heikkinen M, Nurminen V, Hiltunen Y. 2006. Neural network based method for analysis of eps-batch process. In: Juuso E (ed.) , SIMS 2006 Proceedings of The 47th Conference on Simulation and Modelling.Finnish Society for Automation and SIMS. ss. 288-91. 2006
• Heikkinen M, Nurminen V, Hiltunen Y. 2006. Self-organizing maps for analysis of EPS-batch process. In: (ed.) , ALSIS '06 Ist IFAC Workshop on Applications of Large Scale Industrial Systems.IFAC, FSA. ss. 2006
• Hiltunen Y, Heikkinen M, Hiltunen T, Räsänen T, Huhtinen J, Kettunen A. 2006. A som-based tool for process state monitoring and optimization: Juuso E, SIMS 2006 Proceedings of The 47th Conference on Simulation and Modelling.Finnish Society of Automation and SIMS. 164-169. 2006
• Räsänen T, Kettunen A, Niemitalo E, Hiltunen Y. 2006. Self-refreshing SOM for dynamic process state monitoring in a circulating fluidized bed energy plant. In: (ed.) , IS06 2006 3rd International IEEE Conference "Intelligent Systems.IEEE IM/SMC and Harrow School of Computer Science. ss. 344-349. 2006
• Räsänen T, Soukka R, Kokki S, Hiltunen T, Heikkinen M, Kuivalainen R, Hiltunen Y. 2006. Data-based approaches improving the accuracy of life cycle profit models, ALSIS '06 Ist IFAC Workshop on Applications of Large Scale Industrial Systems.IFAC, FSA. 2006
• Heikkinen M, Kettunen A, Niemitalo E, Kuivalainen R, Hiltunen Y. 2005. Application of self-organizing maps for process state monitoring and optimization: Lecoeuche S, Tsaptsinos D, Novel Applications of Neural Networks in Engineering. Proceedings of the Ninth International Conference on Engineering Applications of Neural Nerworks.Ecole des Mines de Douai. 79-83. 2005
• Heikkinen M, Kettunen A, Niemitalo E, Kuivalainen R, Hiltunen Y. 2005. SOM-Based method for process state monitoring and optimization in fluidized bed energy plant. In: Duch W, Kacprzyk J, Oja E, Zadrozny S (ed.) , Artificial Neural networks: Biological Inspirations - ICANN 2005. 15th International Conference. Proceedings, Part I.Springer. Lecture Notes in Computer Science. ss. 409-414. 2005