Harri Niska

A Novel Multi-Objective Hybrid Evolutionary-Based Approach for Tuning Machine Learning Models in Short-Term Power Consumption Forecasting

Vakhnin, Aleksei; Ryzhikov, Ivan; Niska, Harri; Kolehmainen, Mikko. 2024. AI. 5: 2461-2496 A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä

Weather-Based Prediction of Power Consumption in District Heating Network: Case Study in Finland

Vakhnin, Aleksei; Ryzhikov, Ivan; Brester, Christina; Niska, Harri; Kolehmainen, Mikko. 2024. Energies. 17: A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä

A physical-neural network approach for residential load forecasting with dynamic load control

Nakabi, T; Brester, C; Kolehmainen, M; Niska, H. Teoksessa: (toim.) , 2023. 27th International Conference on Electricity Distribution (CIRED 2023). s. 1-5. Institution of engineering and technology A4 Artikkeli konferenssijulkaisussa

Automated load control detection using power quality data and machine learning

Brester, C; Hildén, A; Kolehmainen, M; Pakonen, P; Niska, H. Teoksessa: (toim.) , 2023. 27th International Conference on Electricity Distribution (CIRED 2023). s. 1-5. Institution of engineering and technology A4 Artikkeli konferenssijulkaisussa

Evaluating neural network models in site-specific solar PV forecasting using numerical weather prediction data and weather observations

Brester, Christina; Kallio-Myers, Viivi; Lindfors, Anders V.; Kolehmainen, Mikko; Niska, Harri. 2023. Renewable energy. 207: 266-274 A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä

Aggregated forecasting of the load control responses using a hybrid model that combines a physically based model with machine learning

Koponen, Pekka; Salmi, Tuukka; Evens, Corentin; Takala, Suvi; Hyttinen, Antti; Brester, Christina; Kolehmainen, Mikko; Niska, Harri. Teoksessa: (toim.) , 2021. . s. 588-901. A4 Artikkeli konferenssijulkaisussa

Weather-Driven Predictive Control of a Battery Storage for Improved Microgrid Resilience

Gutierrez-Rojas, Daniel; Mashlakov, Aleksei; Brester, Christina; Niska, Harri; Kolehmainen, Mikko; Narayanan, Arun; Honkapuro, Samuli; Nardelli, Pedro HJ. 2021. IEEE access. 9: 163108-163121 A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä

Assessing and Comparing Short Term Load Forecasting Performance

Koponen, Pekka; Ikäheimo, Jussi; Koskela, Juha; Brester, Christina; Niska, Harri. 2020. Energies. 13: 2054 A2 Katsausartikkeli tieteellisessä aikakauslehdessä

Weather-based fault prediction in electricity networks with artificial neural networks

Brester, Christina; Niska, Harri; Ciszek, Robert ; Kolehmainen, Mikko. Teoksessa: -(toim.) , 2020. 2020 IEEE Congress on Evolutionary Computation (CEC): Conference proceedings. s. 1-8. IEEE A4 Artikkeli konferenssijulkaisussa

Combining the strengths of different load modeling methods in short-term load forecasting of a distribution grid area with active demand

Koponen, Pekka; Niska, Harri; Mutanen, Antti. Teoksessa: -(toim.) , 2019. CIGRE SC D2 Colloquium 2019 - Helsinki, Finland, 11- 14 Jun 2019. s. 1-8. Conseil international des grands réseaux électriques D2 Artikkeli ammatillisessa kokoomateoksessa (ml. toimittajan kirjoittama johdantoartikkeli)

Mitigating the Weaknesses of Machine Learning in Short-Term Forecasting of Aggregated Power System Active Loads

Koponen, Pekka; Niska, Harri; Mutanen, Antti. Teoksessa: -(toim.) , 2019. Proceedings: 2019 IEEE 17th International Conference on Industrial Informatics (INDIN). s. 303-310. IEEE A4 Artikkeli konferenssijulkaisussa

Data analytics approach to create waste generation profiles for waste management and collection

Niska, Harri; Serkkola, Ari. 2018. Waste management. 77: 477-485 A2 Katsausartikkeli tieteellisessä aikakauslehdessä

Effects of Electric Vehicles and Heat Pumps on Long-Term Electricity Consumption Scenarios for Rural Areas in the Nordic Environment

Haakana, Juha; Haapaniemi, Jouni; Lassila, Jukka; Partanen, Jarmo; Niska, Harri; Rautiainen, Antti. Teoksessa: -(toim.) , 2018. 15th International Conference on the European Energy Market (EEM). s. 1-5. A4 Artikkeli konferenssijulkaisussa

Improved modelling of electric loads for enabling demand response by applying physical and data-driven models: Project Response

Koponen, Pekka; Hanninen, Seppo; Mutanen, Antti; Koskela, Juha; Rautiainen, Antti; Jarventausta, Pertti; Niska, Harri; Kolehmainen, Mikko; Koivisto, Hannu. Teoksessa: -(toim.) , 2018. 2018 IEEE International Energy conference (ENERGYCON), Limassol, Cyprus, 3-7 June 2018. s. 354-359. IEEE A4 Artikkeli konferenssijulkaisussa

Hybrid model for short-term forecasting of loads and load control responses

Koponen Pekka, Niska Harri. Teoksessa: -(toim.) , 2017. 2016 IEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT-Europe). s. 1-6. A4 Artikkeli konferenssijulkaisussa

Forest Industry Hygiene Control with Reference to Waste Refinement

Hakalehto Elias, Heitto Anneli, Niska Harri, Suhonen Anssi, Laatikainen Reino, Heitto Lauri, Antikainen Eero, Jääskeläinen Ari. Teoksessa: Eino Elias Hakalehto(toim.) , 2016. Microbiological Industrial Hygiene. s. 151-185. Nova science publishers A3 Kirjan tai muun kokoomateoksen osa

Identifying socio-demographically favourable area types for early hybrid electric vehicle adoption through mining of public sector data

Saarenpää Jukka, Kolehmainen Mikko, Niska Harri. 2016. Intelligent data analysis. 20: 339-355 A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä

Mining smart meter data -case Finland

Mutanen Antti, Järventausta Pertti, Niska Harri. Teoksessa: -(toim.) , 2016. IET Conference Publications.CIRED 2016 Workshop 14-15 June 2016. s. 120. Cired A4 Artikkeli konferenssijulkaisussa

Retrieval of aerosol optical depth from surface solar radiation measurements using machine learning algorithms, non-linear regression and a radiative transfer-based look-up table

Huttunen Jani, Kokkola Harri, Mielonen Tero, Mononen Mika Esa Juhani, Lipponen Antti, Reunanen Juha, Lindfors Anders Vilhelm, Mikkonen Santtu, Lehtinen Kari Erkki Juhani, Kouremeti Natalia, Bais Alkiviadis, Niska Harri, Arola Antti. 2016. Atmospheric chemistry and physics. 16: 8181-8191 A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä

A data mining approach for producing small area statistics-based load profiles for distribution network planning

Saarenpää Jukka, Kolehmainen Mikko, Mononen Matti, Niska Harri. Teoksessa: IEEE(toim.) , 2015. IEEE ICIT 2015 Proceedings. s. 1236-1240. IEEE A4 Artikkeli konferenssijulkaisussa

Evolving smart meter data driven model for short-term forecasting of electric loads

Niska Harri, Koponen, Pekka, Mutanen, Antti. Teoksessa: Palaniswami, Marimuthu Swami, Tan, Hwee Pink(toim.) , 2015. IEEE ISSNIP 2015 Proceedings. s. 1-6. A4 Artikkeli konferenssijulkaisussa

Monetary impact of dynamic pricing and demand response on households: the winners and losers

Mononen Matti, Rautiainen Antti, Saarenpää Jukka, Kolehmainen Mikko, Niska Harri. Teoksessa: 2015 IEEE Power & Energy Society(toim.) , 2015. IEEE Conference Publications. s. 1-5. IEEE A4 Artikkeli konferenssijulkaisussa

Optimized Curve Design For Image Analysis Using Localized Geodesic Distance Transformations

Braithwaite Billy, Niska Harri, Pöllänen Irene, Ikonen Tiia, Haataja Keijo, Toivanen Pekka J., Tolonen Teemu. 2015. Proceedings of SPIE : the International Society for Optical Engineering

Assessment of Some Methods for Short-Term Load Forecasting

Koponen Pekka, Mutanen Antti, Niska Harri. Teoksessa: -(toim.) , 2014. Proceedings of IEEE ISGT Europe 2014. s. 6 s. Institute of Electrical and Electronics Engineers IEEE A4 Artikkeli konferenssijulkaisussa

Computer-aided breast cancer histopathological diagnosis: Comparative analysis of three DTOCS-based features: SW-DTOCS, SW-WDTOCS and SW-3-4-DTOCS

Pöllänen Irene, Braithwaite Billy, Ikonen Tiia, Niska Harri, Haataja Keijo, Toivanen Pekka, Tolonen Teemu. Teoksessa: -(toim.) , 2014. Proceedings of 4th International Conference on Image Processing Theory, Tools, and Applications (IPTA2014). s. 1-6. IEEE A4 Artikkeli konferenssijulkaisussa

Computer-assisted image analysis of histopathological breast cancer images using step-DTOCS

Ikonen Tiia, Niska Harri, Braithwaite Billy, Pöllänen Irene, Haataja Keijo, Toivanen Pekka, Tolonen Teemu, Isola Jorma. Teoksessa: -(toim.) , 2014. Proceedings of the 14th International Conference on Hybrid Intelligent Systems (HIS2014. s. 187-192. A4 Artikkeli konferenssijulkaisussa

Data-driven method for providing feedback to households on electricity consumption

Mononen Matti, Saarenpää Jukka, Johansson Markus, Niska Harri. Teoksessa: -(toim.) , 2014. Proceedings of International Conference on Intelligent Sensing and Information Processing. s. -. IEEE A4 Artikkeli konferenssijulkaisussa

A regional model for sustainable biogas electricity production: A case study from a Finnish province

Huopana Tuomas, Song Han, Kolehmainen Mikko, Niska Harri. 2013. Applied energy. 102: 676-686 A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä

Computational approach for spatiotemporal modelling of heating loads using AMR and other external data

Niska Harri; Saarenpää Jukka; Kolehmainen Mikko. Teoksessa: Pilo, F; Lama, R; Caro Moron, F. J.(toim.) , 2013. CIRED 2013: 22nd International Conference and Exhibition on Electricity Distribution. s. 23/27. IET Services Ltd A4 Artikkeli konferenssijulkaisussa

Extracting controllable heating loads from aggregated smart meter data using clustering and predictive modelling

Niska Harri. Teoksessa: M. Palaniswami, C. Leckie, S. Kanhere, J. Gubbi(toim.) , 2013. IEEE Eight International Conference on Intelligent Sensors, Sensor Networks and Information Processing. s. 368-373. A4 Artikkeli konferenssijulkaisussa

DDM/CI methods and experiments in load modelling using AMR and other environmental data

Niska Harri, Saarenpää Jukka. 2011. VTT Working Papers. . Valtion taloudellinen tutkimuskeskus C1 Kustannettu tieteellinen erillisteos

Data-based method for creating electricity use load profiles using large amount of customer-specific hourly measured electricity use data

Räsänen T, Voukantsis D, Niska H, Karatzas K & Kolehmainen M. 2010. Applied energy. 87: 3538-3545 A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä

Neural networks for the prediction of species-specific stem volumes using airborne laser scanning and aerial photographs

Niska H, Packalén P, Skön J-P, Tokola T, Maltamo M & Kolehmainen M. 2010. IEEE transactions on geoscience and remote sensing. 48: 1076-1085 A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä

Use of sewer on-line total solids data in wastewater treatment plant modelling

Poutiainen H, Niska H, Heinonen-Tanski H & Kolehmainen M. 2010. Water science and technology. 62: 743-750 A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä

An experimental evaluation of ZCS-DM for the prediction of urban air quality

Tzima FA, Niska H, Kolehmainen M, Karatzas KD, Mitkas PA. Teoksessa: Athanasiadis IN, Mitkas PA, Rizzoli AE, Marx-Gómez J(toim.) , 2009. Information Technologies in Environmental Engineering. Proceedings of the 4th International ICSC Symposium. s. 291-304. A4 Artikkeli konferenssijulkaisussa

Neural networks for estimating net ecosystem CO2 exchange using incomplete eddy covariance data

Niska H, Shurpali N, Martikainen P, Kolehmainen M. Teoksessa: Fonseca I Casas, P(toim.) , 2009. Proceedings of the 18th IASTED International Conference on Applied Simulation and Modelling. s. 112-117. A4 Artikkeli konferenssijulkaisussa

Predictive system for monitoring regional visitor attendance levels in large recreational areas

Räsänen T, Niska H, Hiltunen T, Tiirikainen J, Kolehmainen M. 2009. Journal of environmental informatics. 13: 45-55 A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä

Characterisation of the chemical and biological properties of molecules with QSAR/QSPR and chemical grouping, and its application to a group of alkyl ethers

Niska H, Tuppurainen K, Skön J-P, Mallett AK, Kolehmainen M. 2008. Sar and qsar in environmental research. 19: 263-284 A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä

Explaining atmospheric aerosol nucleation events using data mining tools, back-trajectories and land cover characteristics

Junninen H, Hyvönen S, Niska H, Laakso L, Dal Maso M, Grönholm T, Bonn B, Keronen P, Aalto P, Hiltunen V, Pohja T, Launiainen S, Hari P, Mannila H, Kulmala M. Teoksessa: (toim.) , 2006. 7th International Aerosol Conference 2006. Abstract Book. s. . AAAR A4 Artikkeli konferenssijulkaisussa

Genetic algorithms and sensitivity analysis applied to select inputs of a multi-layer perceptron for the prediction of air pollutant time-series

Niska H, Heikkinen M, Kolehmainen M. Teoksessa: (toim.) , 2006. Intelligent Data Engineering and Automated Learning. IDEAL 2006. 7th International Conference, Proceedings. s. 224-231. Springer A4 Artikkeli konferenssijulkaisussa

Improved route planning and scheduling of waste collection and transport

Nuortio T, Kytöjoki J, Niska H, Bräysy O. 2006. Expert systems with applications. 30: 223-232 A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä

Evaluation of an integrated modeling system containing a multi-layer perceptron model and the numerical weather prediction model HIRLAM for the forecasting of urban airborne pollutant concentrations

Niska H, Rantamäki M, Hiltunen T, Karppinen A, Kukkonen J, Ruuskanen J, Kolehmainen M. 2005. Atmospheric environment. 39: 6524-6536 A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä

Evolutionary design and evaluation of modeling system for forecasting urban airborne maximum pollutant concentrations

Niska H, Hiltunen T, Karppinen A, Kolehmainen M. Teoksessa: Ribeiro B, Albrecht RF, Dobnikar A, Pearson DW, Steele NC(toim.) , 2005. Adaptive and Natural Computing Algorithms. Proceedings of the International Conference. s. 181-184. Springer A4 Artikkeli konferenssijulkaisussa

Extensive evaluation of neural network models for the prediction of NO2 and PM10 concentrations, compared with a deterministic modelling system and measurements in central Helsinki

Kukkonen J, Partanen L, Karppinen A, Ruuskanen J, Junninen H, Kolehmainen M, Niska H, Dorling S, Chatterton T, Foxall R, Cawley G. 2003. Atmospheric environment. 37: 4539-4550 A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä

Hybrid models for forecasting air pollution episodes

Niska H, Hiltunen T, Kolehmainen M, Ruuskanen J. Teoksessa: David W. Pearson, Nigel C. Steele, Rudolf F. Albrech(toim.) , 2003. Artificial Neural Nets and Cenetic Algorithms Proceedings of the International Conference. s. 80-84. Springer-Verlag A4 Artikkeli konferenssijulkaisussa

Tarkenna hakuasi

Avainsanat

A Novel Multi-Objective Hybrid Evolutionary-Based Approach for Tuning Machine Learning Models in Short-Term Power Consumption Forecasting

Weather-Based Prediction of Power Consumption in District Heating Network: Case Study in Finland

A physical-neural network approach for residential load forecasting with dynamic load control

Automated load control detection using power quality data and machine learning

Evaluating neural network models in site-specific solar PV forecasting using numerical weather prediction data and weather observations

Aggregated forecasting of the load control responses using a hybrid model that combines a physically based model with machine learning

Weather-Driven Predictive Control of a Battery Storage for Improved Microgrid Resilience

Assessing and Comparing Short Term Load Forecasting Performance

Weather-based fault prediction in electricity networks with artificial neural networks

Combining the strengths of different load modeling methods in short-term load forecasting of a distribution grid area with active demand

Mitigating the Weaknesses of Machine Learning in Short-Term Forecasting of Aggregated Power System Active Loads

Data analytics approach to create waste generation profiles for waste management and collection

Effects of Electric Vehicles and Heat Pumps on Long-Term Electricity Consumption Scenarios for Rural Areas in the Nordic Environment

Improved modelling of electric loads for enabling demand response by applying physical and data-driven models: Project Response

Hybrid model for short-term forecasting of loads and load control responses

Forest Industry Hygiene Control with Reference to Waste Refinement

Identifying socio-demographically favourable area types for early hybrid electric vehicle adoption through mining of public sector data

Mining smart meter data -case Finland

Retrieval of aerosol optical depth from surface solar radiation measurements using machine learning algorithms, non-linear regression and a radiative transfer-based look-up table

A data mining approach for producing small area statistics-based load profiles for distribution network planning

Evolving smart meter data driven model for short-term forecasting of electric loads

Monetary impact of dynamic pricing and demand response on households: the winners and losers

Optimized Curve Design For Image Analysis Using Localized Geodesic Distance Transformations

Assessment of Some Methods for Short-Term Load Forecasting

Computer-aided breast cancer histopathological diagnosis: Comparative analysis of three DTOCS-based features: SW-DTOCS, SW-WDTOCS and SW-3-4-DTOCS

Computer-assisted image analysis of histopathological breast cancer images using step-DTOCS

Data-driven method for providing feedback to households on electricity consumption

A regional model for sustainable biogas electricity production: A case study from a Finnish province

Computational approach for spatiotemporal modelling of heating loads using AMR and other external data

Extracting controllable heating loads from aggregated smart meter data using clustering and predictive modelling

DDM/CI methods and experiments in load modelling using AMR and other environmental data

Data-based method for creating electricity use load profiles using large amount of customer-specific hourly measured electricity use data

Neural networks for the prediction of species-specific stem volumes using airborne laser scanning and aerial photographs

Use of sewer on-line total solids data in wastewater treatment plant modelling

An experimental evaluation of ZCS-DM for the prediction of urban air quality

Neural networks for estimating net ecosystem CO2 exchange using incomplete eddy covariance data

Predictive system for monitoring regional visitor attendance levels in large recreational areas

Characterisation of the chemical and biological properties of molecules with QSAR/QSPR and chemical grouping, and its application to a group of alkyl ethers

Explaining atmospheric aerosol nucleation events using data mining tools, back-trajectories and land cover characteristics

Genetic algorithms and sensitivity analysis applied to select inputs of a multi-layer perceptron for the prediction of air pollutant time-series

Improved route planning and scheduling of waste collection and transport

Evaluation of an integrated modeling system containing a multi-layer perceptron model and the numerical weather prediction model HIRLAM for the forecasting of urban airborne pollutant concentrations

Evolutionary design and evaluation of modeling system for forecasting urban airborne maximum pollutant concentrations

Evolving the neural network model for forecasting air pollution time series

Methods for imputation of missing values in air quality data sets

Evolving the neural network model for forecasting air pollution time series

Extensive evaluation of neural network models for the prediction of NO2 and PM10 concentrations, compared with a deterministic modelling system and measurements in central Helsinki

Hybrid models for forecasting air pollution episodes