Mikko Kolehmainen
Mikko Kolehmainen
Professor of environmental informatics and modelling, University of Eastern Finland
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Zitiert von
Zitiert von
Analysis of gene expression data using self‐organizing maps
P Törönen, M Kolehmainen, G Wong, E Castrén
FEBS letters 451 (2), 142-146, 1999
Methods for imputation of missing values in air quality data sets
H Junninen, H Niska, K Tuppurainen, J Ruuskanen, M Kolehmainen
Atmospheric environment 38 (18), 2895-2907, 2004
Cow behaviour pattern recognition using a three-dimensional accelerometer and support vector machines
P Martiskainen, M Järvinen, JP Skön, J Tiirikainen, M Kolehmainen, ...
Applied animal behaviour science 119 (1-2), 32-38, 2009
Neural networks and periodic components used in air quality forecasting
M Kolehmainen, H Martikainen, J Ruuskanen
Atmospheric Environment 35 (5), 815-825, 2001
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
J Kukkonen, L Partanen, A Karppinen, J Ruuskanen, H Junninen, ...
Atmospheric Environment 37 (32), 4539-4550, 2003
Evolving the neural network model for forecasting air pollution time series
H Niska, T Hiltunen, A Karppinen, J Ruuskanen, M Kolehmainen
Engineering Applications of Artificial Intelligence 17 (2), 159-167, 2004
Intercomparison of air quality data using principal component analysis, and forecasting of PM10 and PM2. 5 concentrations using artificial neural networks, in Thessaloniki and …
D Voukantsis, K Karatzas, J Kukkonen, T Räsänen, A Karppinen, ...
Science of the Total Environment 409 (7), 1266-1276, 2011
Data-based method for creating electricity use load profiles using large amount of customer-specific hourly measured electricity use data
T Räsänen, D Voukantsis, H Niska, K Karatzas, M Kolehmainen
Applied Energy 87 (11), 3538-3545, 2010
A rigorous inter-comparison of ground-level ozone predictions
U Schlink, S Dorling, E Pelikan, G Nunnari, G Cawley, H Junninen, ...
Atmospheric Environment 37 (23), 3237-3253, 2003
Feature-based clustering for electricity use time series data
T Räsänen, M Kolehmainen
Adaptive and Natural Computing Algorithms: 9th International Conference …, 2009
Reducing energy consumption by using self-organizing maps to create more personalized electricity use information
T Räsänen, J Ruuskanen, M Kolehmainen
Applied Energy 85 (9), 830-840, 2008
Financial innovation: Credit default hybrid model for SME lending
K Li, J Niskanen, M Kolehmainen, M Niskanen
Expert Systems with Applications 61, 343-355, 2016
Geodemographic analysis and estimation of early plug-in hybrid electric vehicle adoption
J Saarenpää, M Kolehmainen, H Niska
Applied Energy 107, 456-464, 2013
Forecasting air quality parameters using hybrid neural network modelling
M Kolehmainen, H Martikainen, T Hiltunen, J Ruuskanen
Environmental Monitoring and Assessment 65, 277-286, 2000
Intelligent analysis of energy consumption in school buildings
M Raatikainen, JP Skön, K Leiviskä, M Kolehmainen
Applied energy 165, 416-429, 2016
Neural networks for the prediction of species-specific plot volumes using airborne laser scanning and aerial photographs
H Niska, JP Skon, P Packalen, T Tokola, M Maltamo, M Kolehmainen
IEEE Transactions on Geoscience and Remote Sensing 48 (3), 1076-1085, 2009
Evaluation of an integrated modelling system containing a multi-layer perceptron model and the numerical weather prediction model HIRLAM for the forecasting of urban airborne …
H Niska, M Rantamäki, T Hiltunen, A Karppinen, J Kukkonen, ...
Atmospheric Environment 39 (35), 6524-6536, 2005
Evaluating online data of water quality changes in a pilot drinking water distribution system with multivariate data exploration methods
SM Mustonen, S Tissari, L Huikko, M Kolehmainen, MJ Lehtola, ...
Water Research 42 (10-11), 2421-2430, 2008
Gene expression responses of paper birch (Betula papyrifera) to elevated CO2 and O3 during leaf maturation and senescence
S Kontunen-Soppela, J Parviainen, H Ruhanen, M Brosché, M Keinänen, ...
Environmental pollution 158 (4), 959-968, 2010
Determination and identification of pesticides from liquid matrices using ion mobility spectrometry
K Tuovinen, M Kolehmainen, H Paakkanen
Analytica chimica acta 429 (2), 257-268, 2001
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