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, 4, 2461-2496. A1 Journal article (refereed), original research

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, 12, 2840. A1 Journal article (refereed), original research

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

Nakabi, T; Brester, C; Kolehmainen, M; Niska, H, 2023, 27th International Conference on Electricity Distribution (CIRED 2023), 1-5. A4 Conference proceedings

Automated load control detection using power quality data and machine learning

Brester, C; Hildén, A; Kolehmainen, M; Pakonen, P; Niska, H, 2023, 27th International Conference on Electricity Distribution (CIRED 2023), 1-5. A4 Conference proceedings

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 Journal article (refereed), original research

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, 2021, 588-901. A4 Conference proceedings

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 Journal article (refereed), original research

Assessing and Comparing Short Term Load Forecasting Performance

Koponen, Pekka; Ikäheimo, Jussi; Koskela, Juha; Brester, Christina; Niska, Harri, 2020, Energies, 13, 8, 2054. A2 Review article, Literature review, Systematic review

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

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

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, 2019, -, CIGRE SC D2 Colloquium 2019 - Helsinki, Finland, 11- 14 Jun 2019, 1-8. D2 Article in a professional book (incl. an introduction by the editor)

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

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

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

Niska, Harri; Serkkola, Ari, 2018, Waste management, 77, 477-485. A2 Review article, Literature review, Systematic review

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, 2018, -, 15th International Conference on the European Energy Market (EEM), 1-5. A4 Conference proceedings

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, 2018, -, 2018 IEEE International Energy conference (ENERGYCON), Limassol, Cyprus, 3-7 June 2018, 354-359, IEEE international energy conference. A4 Conference proceedings

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

Koponen Pekka, Niska Harri, 2017, -, 2016 IEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT-Europe), 1-6, IEEE pes conference on innovative smart grid technologies. A4 Conference proceedings

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, 2016, Eino Elias Hakalehto, Microbiological Industrial Hygiene, 151-185. A3 Book section, Chapters in research books

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, 2, 339-355. A1 Journal article (refereed), original research

Mining smart meter data -case Finland

Mutanen Antti, Järventausta Pertti, Niska Harri, 2016, -, IET Conference Publications.CIRED 2016 Workshop 14-15 June 2016, 120, International conference on electricity distribution workshop. A4 Conference proceedings

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 Journal article (refereed), original research

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

Saarenpää Jukka, Kolehmainen Mikko, Mononen Matti, Niska Harri, 2015, IEEE, IEEE ICIT 2015 Proceedings, 1236-1240, IEEE International Conference on Industrial Technology. A4 Conference proceedings

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

Niska Harri, Koponen, Pekka, Mutanen, Antti, 2015, Palaniswami, Marimuthu Swami, Tan, Hwee Pink, IEEE ISSNIP 2015 Proceedings, 1-6, International Conference on Intelligent Sensors, Sensor Networks and Information Processing. A4 Conference proceedings

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

Mononen Matti, Rautiainen Antti, Saarenpää Jukka, Kolehmainen Mikko, Niska Harri, 2015, 2015 IEEE Power & Energy Society, IEEE Conference Publications, 1-5, IEEE pes conference on innovative smart grid technologies. A4 Conference proceedings

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, 2014, -, Proceedings of IEEE ISGT Europe 2014, 6 s, IEEE pes innovative smart grid technologies conference. A4 Conference proceedings

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, 2014, -, Proceedings of 4th International Conference on Image Processing Theory, Tools, and Applications (IPTA2014), 1-6, International Conference on Image Processing Theory, Tools and Applications. A4 Conference proceedings

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, 2014, -, Proceedings of the 14th International Conference on Hybrid Intelligent Systems (HIS2014, 187-192, International Conference on Hybrid Intelligent Systems. A4 Conference proceedings

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

Mononen Matti, Saarenpää Jukka, Johansson Markus, Niska Harri, 2014, -, Proceedings of International Conference on Intelligent Sensing and Information Processing, International Conference on Intelligent Sensors, Sensor Networks and Information Processing. A4 Conference proceedings

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 Journal article (refereed), original research

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

Niska Harri; Saarenpää Jukka; Kolehmainen Mikko, 2013, Pilo, F; Lama, R; Caro Moron, F. J., CIRED 2013: 22nd International Conference and Exhibition on Electricity Distribution, 23/27, International Conference and Exhibition on Electricity Distribution. A4 Conference proceedings

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

Niska Harri, 2013, M. Palaniswami, C. Leckie, S. Kanhere, J. Gubbi, IEEE Eight International Conference on Intelligent Sensors, Sensor Networks and Information Processing, 368-373, International Conference on Intelligent Sensors, Sensor Networks and Information Processing. A4 Conference proceedings

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

Niska Harri, Saarenpää Jukka, 2011, Valtion taloudellinen tutkimuskeskus. C1 Book

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, 11, 3538-3545. A1 Journal article (refereed), original research

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, 3, 1076-1085. A1 Journal article (refereed), original research

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, 4, 743-750. A1 Journal article (refereed), original research

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

Tzima FA, Niska H, Kolehmainen M, Karatzas KD, Mitkas PA, 2009, Athanasiadis IN, Mitkas PA, Rizzoli AE, Marx-Gómez J, Information Technologies in Environmental Engineering. Proceedings of the 4th International ICSC Symposium, 291-304. A4 Conference proceedings

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

Niska H, Shurpali N, Martikainen P, Kolehmainen M, 2009, Fonseca I Casas, P, Proceedings of the 18th IASTED International Conference on Applied Simulation and Modelling, 112-117. A4 Conference proceedings

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, 1, 45-55. A1 Journal article (refereed), original research

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, 3-4, 263-284. A1 Journal article (refereed), original research

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, 2006, 7th International Aerosol Conference 2006. Abstract Book. A4 Conference proceedings

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, 2006, Intelligent Data Engineering and Automated Learning. IDEAL 2006. 7th International Conference, Proceedings, 224-231. A4 Conference proceedings

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 Journal article (refereed), original research

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 Journal article (refereed), original research

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

Niska H, Hiltunen T, Karppinen A, Kolehmainen M, 2005, Ribeiro B, Albrecht RF, Dobnikar A, Pearson DW, Steele NC, Adaptive and Natural Computing Algorithms. Proceedings of the International Conference, 181-184. A4 Conference proceedings

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 Journal article (refereed), original research

Hybrid models for forecasting air pollution episodes

Niska H, Hiltunen T, Kolehmainen M, Ruuskanen J, 2003, David W. Pearson, Nigel C. Steele, Rudolf F. Albrech, Artificial Neural Nets and Cenetic Algorithms Proceedings of the International Conference, 80-84. A4 Conference proceedings

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Keywords

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