M. Kanevski

发表

Environmental and Pollution Data Mapping with Support Vector Regression

S. Canu, M. Kanevski, 2003 .

Active Learning Methods for Remote Sensing Image Classification

William J. Emery, Mikhail F. Kanevski, Fabio Pacifici, 2009, IEEE Transactions on Geoscience and Remote Sensing.

Spatio-temporal modelling and uncertainty estimation of hourly global solar irradiance using Extreme Learning Machines

R. Castello, M. Kanevski, Nahid Mohajeri, 2019, Energy Procedia.

Long-range fluctuations and multifractality in connectivity density time series of a wind speed monitoring network.

Mikhail Kanevski, Luciano Telesca, Mohamed Laib, 2017, Chaos.

The multipoint Morisita index for the analysis of spatial patterns

M. Kanevski, J. Golay, C. Orozco, 2013, 1307.3756.

Analysis and modelling of spatial environmental data

M. Kanevski, M. Maignan, 2004 .

Periodic fluctuations in correlation-based connectivity density time series: Application to wind speed-monitoring network in Switzerland

L. Telesca, M. Kanevski, M. Laib, 2017, 1708.03782.

Applying machine learning methods to avalanche forecasting

R. Purves, M. Kanevski, A. Pozdnoukhov, 2008, Annals of Glaciology.

Multi-Scale Support Vector Regression for Hot Spot Detection and Modeling

M. Kanevski, A. Pozdnoukhov, 2007 .

Natural Hazards and Earth System Sciences Spatio-temporal avalanche forecasting with Support Vector Machines

R. Purves, M. Kanevski, G. Matasci, 2011 .

Reservoir Modelling Under Uncertainty - A Kernel Learning Approach

A. Pozdnoukhov, M. Kanevski, M. Christie, 2012 .

Extreme Precipitation Modelling Using Geostatistics and Machine Learning Algorithms

Devis Tuia, Alexei Pozdnoukhov, Mikhail Kanevski, 2010 .

Local fractality: The case of forest fires in Portugal

Mário G. Pereira, M. Kanevski, 2016, 1611.07797.

Multifractal portrayal of the Swiss population

Mikhail Kanevski, Jean Golay, M. Kanevski, 2013, 1308.4038.

A Comparison of One-Class Classifiers for Novelty Detection in Forensic Case Data

Mikhail F. Kanevski, Pierre Esseiva, Anne-Laure Terrettaz-Zufferey, 2007, IDEAL.

Investigating the time dynamics of wind speed in complex terrains by using the Fisher–Shannon method

L. Telesca, M. Kanevski, Fabian Guignard, 2018, Physica A: Statistical Mechanics and its Applications.

Power spectrum and multifractal detrended fluctuation analysis of high-frequency wind measurements in mountainous regions

Mikhail Kanevski, Luciano Telesca, Michele Lovallo, 2016 .

Analysis of temporal properties of extremes of wind measurements from 132 stations over Switzerland

L. Telesca, M. Kanevski, Fabian Guignard, 2020 .

Analysis of temporal properties of extremes of wind measurements from 132 stations over Switzerland

L. Telesca, M. Kanevski, Fabian Guignard, 2018, Renewable Energy.

Forest Fires in a Random Forest

Mikhail Kanevski, Michael Leuenberger, Carmen Vega Orozco, 2013 .

Linearity versus non-linearity in high frequency multilevel wind time series measured in urban areas

L. Telesca, M. Kanevski, Fabian Guignard, 2018, Chaos, Solitons & Fractals.

COMBINING NEURAL NETWORKS WITH KRIGING FOR STOCHASTIC RESERVOIR MODELING

M. Kanevski, T. Gedeon, L. Wang, 2021 .

Advanced Mapping of Environmental Data: Introduction

M. Kanevski, 2010 .

Wavelet variance scale-dependence as a dynamics discriminating tool in high-frequency urban wind speed time series

L. Telesca, M. Kanevski, Fabian Guignard, 2018, Physica A: Statistical Mechanics and its Applications.

Analysis of high dimensional environmental data using local fractality concept and machine learning

M. Kanevski, M. Laib, 2018 .

Morisita-based space-clustering analysis of Swiss seismicity

L. Telesca, M. Kanevski, J. Golay, 2015 .

Geostatistical and Artificial Neuronal Networks maps of the Texture of the soils of Geneva Canton

Mikhail F. Kanevski, Michel Maignan, A. Besson, 2004, EnviroInfo.

Data-Driven Topographic Feature Selection for Mean Wind Speed Mapping

L. Foresti, M. Kanevski, A. Pozdnoukhov, 2009 .

Local fractality: The case of forest fires in Portugal

Mário G. Pereira, M. Kanevski, M. Pereira, 2016, 1611.07797.

Spatio-temporal estimation of wind speed and wind power using extreme learning machines: predictions, uncertainty and technical potential

M. Kanevski, J. Scartezzini, A. Walch, 2021, Stochastic Environmental Research and Risk Assessment.

A new estimator of intrinsic dimension based on the multipoint Morisita index

Mikhail F. Kanevski, Jean Golay, M. Kanevski, 2014, Pattern Recognit..

Predicting snow height in ski resorts using an agent-based simulation

Mikhail F. Kanevski, Jean-Christophe Loubier, Marc Revilloud, 2013, Multiagent Grid Syst..

Monitoring network optimisation using support vector machines

M. Kanevski, A. Pozdnoukhov, 2005 .

Space-time cluster detection in crime data with scan statistics

Pierre Esseiva, Anne-Laure Terrettaz-Zufferey, Frédéric Ratle, 2007 .

Statistical learning in geoscience modelling: Novel algorithms and challenging case studies

Mikhail F. Kanevski, Vasiliy V. Demyanov, M. Kanevski, 2015, Comput. Geosci..

Special issue: Advances in artificial neural networks, machine learning and computational intelligenceSelected papers from the 23rd European Symposium on Artificial Neural Networks (ESANN 2015)

Mikhail F. Kanevski, Romain Hérault, Fabio Aiolli, 2016, Neurocomputing.

Artificial Snow Optimization in Winter Sport Destinations Using a Multi-agent Simulation

Mikhail F. Kanevski, Jean-Christophe Loubier, Marc Revilloud, 2011, PAAMS.

MFDFA R package : multifractal analysis for time series

L. Telesca, M. Kanevski, M. Laib, 2019 .

Wildfire susceptibility mapping: Deterministic vs. stochastic approaches

Mikhail F. Kanevski, Marj Tonini, Mário G. Pereira, 2018, Environ. Model. Softw..

Advanced Exploratory Analysis of Air Pollution Multivariate Spatio-Temporal Data

M. Kanevski, Fabian Guignard, Federico Amato, 2020 .

Indoor radon distribution in Switzerland: lognormality and Extreme Value Theory.

D. Tuia, M. Kanevski, 2008, Journal of environmental radioactivity.

Determination of Communities at Risk from Thawing Permafrost

M. Kanevski, K. Bjella, B. Connor, 2019, Cold Regions Engineering 2019.

Reservoir Modelling with Feature Selection: Kernel Learning Approach

Michael Andrew Christie, Vasily Demyanov, Mikhail Kanevski, 2011, ANSS 2011.

Uncertainty quantification with support vector regression prediction models

Michael Andrew Christie, Vasily Demyanov, Alexei Pozdnoukhov, 2010 .

Comparing seismicity declustering techniques by means of the joint use of Allan Factor and Morisita index

L. Telesca, M. Kanevski, J. Golay, 2015, Stochastic Environmental Research and Risk Assessment.

Analysis of air pollution time series using complexity-invariant distance and information measures

M. Kanevski, Fabian Guignard, M. Laib, 2019, Physica A: Statistical Mechanics and its Applications.

Community detection analysis in wind speed-monitoring systems using mutual information-based complex network.

Mikhail Kanevski, Luciano Telesca, Fabian Guignard, 2018, Chaos.

Data-driven exploration of orographic enhancement of precipitation

Alexei Pozdnoukhov, Mikhail Kanevski, Loris Foresti, 2010 .

Multi-scale support vector algorithms for hot spot detection and modelling

Alexei Pozdnoukhov, Mikhail Kanevski, M. Kanevski, 2008 .

PRINCIPAL COMPONENT ANALYSIS OF SPATIAL DATA

M. Kanevski, G. Raspa, M. Maignan, 2016 .

Machine Learning Feature Selection Methods for Landslide Susceptibility Mapping

Mikhail Kanevski, Michel Jaboyedoff, Natan Micheletti, 2013, Mathematical Geosciences.

A new algorithm for redundancy minimisation in geo-environmental data

Mikhail Kanevski, Mohamed Laib, M. Kanevski, 2019, Comput. Geosci..

Unsupervised Feature Selection Based on Space Filling Concept pdf

Mikhail Kanevski, Mohamed Laib, M. Kanevski, 2017, ArXiv.

Flooding extent cartography with Landsat TM imagery and regularized kernel Fisher's discriminant analysis

George P. Petropoulos, Mikhail F. Kanevski, Michele Volpi, 2013, Comput. Geosci..

Supervised change detection in VHR images using contextual information and support vector machines

Francesca Bovolo, Lorenzo Bruzzone, Mikhail F. Kanevski, 2013, Int. J. Appl. Earth Obs. Geoinformation.

Detection of Optimal Models in Parameter Space with Support Vector Machines

Michael Andrew Christie, Vasily Demyanov, Alexei Pozdnoukhov, 2010 .

Multiple Kernel Learning of Environmental Data. Case Study: Analysis and Mapping of Wind Fields

Mikhail F. Kanevski, Devis Tuia, Alexei Pozdnoukhov, 2009, ICANN.

Environmental data mining and modeling based on machine learning algorithms and geostatistics

Stéphane Canu, Mikhail F. Kanevski, Michel Maignan, 2004, Environ. Model. Softw..

Support Vector Machines for Classification and Mapping of Reservoir Data Support Vector Machines for Classification and Mapping of Reservoir Data

Stéphane Canu, Mikhail Kanevski, Michel Maignan, 2022 .

Advanced Spatial Data Analysis and Modelling with Support Vector Machines

Stéphane Canu, Alexei Pozdnoukhov, Mikhail Kanevski, 2000 .

Environmental spatial data classification with Support Vector Machines

Eddy Mayoraz, Mikhail Kanevski, Michel Maignan, 1999 .

Numerical Experiments with Support Vector Machines

Mikhail Kanevski, Nicolas Gilardi, N. Gilardi, 1999 .

Automatic Mapping and Classification of Spatial Environmental Data

Alexei Pozdnoukhov, Mikhail Kanevski, V. Timonin, 2011 .

Mapping of environmental data using kernel-based methods

Mikhail F. Kanevski, Alexei Pozdnoukhov, Michel Maignan, 2007, Rev. Int. Géomatique.

Memory-Based Cluster Sampling for Remote Sensing Image Classification

Mikhail F. Kanevski, Michele Volpi, Devis Tuia, 2012, IEEE Transactions on Geoscience and Remote Sensing.

A Survey of Active Learning Algorithms for Supervised Remote Sensing Image Classification

Mikhail F. Kanevski, Michele Volpi, Jordi Muñoz-Marí, 2011, IEEE Journal of Selected Topics in Signal Processing.

Spatial prediction of monthly wind speeds in complex terrain with adaptive general regression neural networks

Mikhail Kanevski, Loris Foresti, Sylvain Robert, 2013 .

Optimization of snowmaking in high mountains ski resorts

Jean-Christophe Loubier, M. Kanevski, Michael Schumacher, 2010, GIScience 2010.

Automatic Decision-Oriented Mapping of Pollution Data

Mikhail F. Kanevski, Alexei Pozdnoukhov, Vadim Timonin, 2008, ICCSA.

Spatio-temporal evolution of global surface temperature distributions

M. Kanevski, Fabian Guignard, Federico Amato, 2020, CI.

Advanced Analysis of Temporal Data Using Fisher-Shannon Information: Theoretical Development and Application in Geosciences

M. Kanevski, Fabian Guignard, M. Laib, 2019, Frontiers in Earth Science.

Multifractal analysis of the time series of daily means of wind speed in complex regions

Mikhail Kanevski, Luciano Telesca, Mohamed Laib, 2017, 1710.01490.

Uncertainty Quantification in Extreme Learning Machine: Analytical Developments, Variance Estimates and Confidence Intervals pdf

Federico Amato, Mikhail Kanevski, Fabian Guignard, 2020, Neurocomputing.

On Feature Selection Using Anisotropic General Regression Neural Network

Philippe Jacquet, Federico Amato, Mikhail Kanevski, 2020, ESANN.

Model Variance for Extreme Learning Machine

Mikhail Kanevski, Fabian Guignard, Mohamed Laib, 2020, ESANN.

Feature Selection for Regression Problems Based on the Morisita Estimator of Intrinsic Dimension: Concept and Case Studies

Mikhail F. Kanevski, Michael Leuenberger, Jean Golay, 2016, Pattern Recognit..

Unsupervised learning of Swiss population spatial distribution.

M. Kanevski, 2021, PloS one.

Unsupervised Learning of High Dimensional Environmental Data Using Local Fractality Concept

M. Kanevski, M. Laib, 2020, ICPR Workshops.

Semisupervised Transfer Component Analysis for Domain Adaptation in Remote Sensing Image Classification

Lorenzo Bruzzone, Michele Volpi, Devis Tuia, 2015, IEEE Transactions on Geoscience and Remote Sensing.

Conditional Gaussian mixture models for environmental risk mapping

Samy Bengio, Mikhail F. Kanevski, N. Gilardi, 2002, Proceedings of the 12th IEEE Workshop on Neural Networks for Signal Processing.

Environmental and Pollution Spatial Data Classification with Support Vector Machines and Geostatistics

Eddy Mayoraz, Mikhail Kanevski, Michel Maignan, 1999 .

Unsupervised Change Detection With Kernels

Gustavo Camps-Valls, Mikhail F. Kanevski, Michele Volpi, 2012, IEEE Geoscience and Remote Sensing Letters.

A novel framework for spatio-temporal prediction of environmental data using deep learning

Mikhail Kanevski, Fabian Guignard, Sylvain Robert, 2020, Scientific Reports.

SVM-Based Boosting of Active Learning Strategies for Efficient Domain Adaptation

Mikhail F. Kanevski, Devis Tuia, Giona Matasci, 2012, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.

Domain separation for efficient adaptive active learning

Mikhail F. Kanevski, Devis Tuia, Giona Matasci, 2011, 2011 IEEE International Geoscience and Remote Sensing Symposium.

Fisher–Shannon Complexity Analysis of High-Frequency Urban Wind Speed Time Series

Mikhail Kanevski, Dasaraden Mauree, Luciano Telesca, 2018, Entropy.

Interest rates mapping

Alexei Pozdnoukhov, Mikhail Kanevski, Michel Maignan, 2007, 0709.4361.

Multi-sensor change detection based on nonlinear canonical correlations

Gustavo Camps-Valls, Mikhail F. Kanevski, Michele Volpi, 2013, 2013 IEEE International Geoscience and Remote Sensing Symposium - IGARSS.

Classification of Interest Rate Curves Using Self-Organising Maps

V. Timonin, M. Maignan, M. Kanevski, 2007, 0709.4401.

Analysis of wind time series using network science and multifractal concept

L. Telesca, M. Kanevski, Fabian Guignard, 2018 .

Advanced Mapping of Environmental Spatial Data: Case Studies

Ross S. Purves, Alexei Pozdnoukhov, Mikhail Kanevski, 2010 .

Support-Based Implementation of Bayesian Data Fusion for Spatial Enhancement: Applications to ASTER Thermal Images

Mikhail F. Kanevski, Devis Tuia, Patrick Bogaert, 2008, IEEE Geoscience and Remote Sensing Letters.

Learning Relevant Image Features With Multiple-Kernel Classification

Gustavo Camps-Valls, Mikhail F. Kanevski, Devis Tuia, 2010, IEEE Transactions on Geoscience and Remote Sensing.

Fuzzy definition of Rural Urban Interface: An application based on land use change scenarios in Portugal

Beniamino Murgante, Mikhail F. Kanevski, Federico Amato, 2018, Environ. Model. Softw..

Classification of Very High Spatial Resolution Imagery Using Mathematical Morphology and Support Vector Machines

William J. Emery, Mikhail F. Kanevski, Fabio Pacifici, 2009, IEEE Transactions on Geoscience and Remote Sensing.

Unsupervised change detection by kernel clustering

Gustavo Camps-Valls, Michele Volpi, Devis Tuia, 2010, Remote Sensing.

Emergence of spatio-temporal patterns in forest-fire sequences

Devis Tuia, Mikhail Kanevski, Rosa Lasaponara, 2008 .

Data-driven mapping of the potential mountain permafrost distribution.

Mikhail Kanevski, Nicola Deluigi, Christophe Lambiel, 2017, The Science of the total environment.

Prediction of Landslide Susceptibility Using logistic Regression: A Case Study in Bailongjiang River Basin, China

Mikhail F. Kanevski, J. Wang, Alexei Pozdnoukhov, 2008, 2008 Fifth International Conference on Fuzzy Systems and Knowledge Discovery.

Understanding angular effects in VHR imagery and their significance for urban land-cover model portability: A study of two multi-angle in-track image sequences

Fabio Pacifici, Devis Tuia, Giona Matasci, 2015 .

Statistical assessment of dataset shift and model portability in multi-angle in-track image acquisitions

Mikhail F. Kanevski, Fabio Pacifici, Devis Tuia, 2013, 2013 IEEE International Geoscience and Remote Sensing Symposium - IGARSS.

Semi-supervised multiview embedding for hyperspectral data classification

Michele Volpi, Devis Tuia, Mikhail Kanevski, 2014, Neurocomputing.

Machine Learning for Spatial Environmental Data: Theory, Applications, and Software

Alexei Pozdnoukhov, Mikhail Kanevski, Vadim Timonin, 2009 .

Wavelet analysis residual kriging vs. neural network residual kriging

Vasily Demyanov, Stéphane Canu, Mikhail Kanevski, 2001 .

Kernel-Based Mapping of Orographic Rainfall Enhancement in the Swiss Alps as Detected by Weather Radar

Mikhail F. Kanevski, Alexei Pozdnoukhov, Loris Foresti, 2012, IEEE Transactions on Geoscience and Remote Sensing.

Spatio-temporal avalanche forecasting with Support Vector Machines

Ross S. Purves, Giona Matasci, Alexei Pozdnoukhov, 2011 .

Unbiased query-by-bagging active learning for VHR image classification

Michele Volpi, Devis Tuia, Mikhail Kanevski, 2010, Remote Sensing.

Data-driven topo-climatic mapping with machine learning methods

Alexei Pozdnoukhov, Mikhail Kanevski, Loris Foresti, 2009 .

Semi-Supervised Support Vector Machine for Natural Hazards Forecasting. Case Study: Snow Avalanches

Ross S. Purves, Mikhail Kanevski, A. Pozdnukhov, 2008 .

Analysis of Interest Rate Curves Clustering Using Self-Organising Maps

M. Kanevski, M. Maignan, A. Pozdnoukhov, 2008 .

Evolution of Interest Rate Curve : Empirical Analysis of Patterns Using Nonlinear Clustering Tools

V. Timonin, M. Maignan, M. Kanevski, 2008 .

Learning wind fields with multiple kernels

Devis Tuia, Alexei Pozdnoukhov, Mikhail Kanevski, 2011 .

Temporal patterns of fire sequences observed in Canton of Ticino (southern Switzerland).

Marj Tonini, Mikhail Kanevski, Luciano Telesca, 2010 .

Spatio-temporal estimation of wind speed and wind power using machine learning: predictions, uncertainty and technical potential pdf

Jean-Louis Scartezzini, Federico Amato, Mikhail Kanevski, 2021, ArXiv.

A Novel Framework for Spatio-Temporal Prediction of Climate Data Using Deep Learning

M. Kanevski, Fabian Guignard, Federico Amato, 2020, ArXiv.

Machine learning for toxicity characterization of organic chemical emissions using USEtox database: Learning the structure of the input space.

Enrico Benetto, Mikhail Kanevski, Antonino Marvuglia, 2015, Environment international.

Unsupervised feature selection based on the Morisita estimator of intrinsic dimension

Mikhail F. Kanevski, Jean Golay, M. Kanevski, 2016, Knowl. Based Syst..

Spatial Modelling of Extreme Wind Speed Distributions in Switzerland

Mikhail Kanevski, Mohamed Laib, M. Kanevski, 2016 .

Cluster-based active learning for compact image classification

Gustavo Camps-Valls, Mikhail F. Kanevski, Devis Tuia, 2010, 2010 IEEE International Geoscience and Remote Sensing Symposium.

Active Learning of Very-High Resolution Optical Imagery with SVM: Entropy vs Margin Sampling

William J. Emery, Fabio Del Frate, Mikhail F. Kanevski, 2008, IGARSS 2008 - 2008 IEEE International Geoscience and Remote Sensing Symposium.

Using active learning for monitoring networks design: the example of wind power plants sites evaluation

Devis Tuia, Alexei Pozdnoukhov, Mikhail Kanevski, 2012 .

Wavelet Scale Variance Analysis of Wind Extremes in Mountainous Terrains

Mikhail Kanevski, Luciano Telesca, Fabian Guignard, 2019, Energies.

Unsupervised feature selection based on the Morisita estimator of intrinsic dimension

M. Kanevski, J. Golay, 2016, Knowl. Based Syst..

Feature selection in environmental data mining combining Simulated Annealing and Extreme Learning Machine

Mikhail F. Kanevski, Michael Leuenberger, M. Kanevski, 2014, ESANN.

Socio-economic Data Analysis with Scan Statistics and Self-organizing Maps

Mikhail F. Kanevski, Devis Tuia, Christian Kaiser, 2008, ICCSA.

Detection of Urban Socio-economic Patterns Using Clustering Techniques

Devis Tuia, Mikhail Kanevski, Christian Kaiser, 2009 .

Clustering and Hot Spot Detection in Socio-economic Spatio-temporal Data

Mikhail F. Kanevski, Devis Tuia, Christian Kaiser, 2009, Trans. Comput. Sci..

Advanced clustering methods for mining chemical databases in forensic science

Christian Gagné, Mikhail Kanevski, Pierre Esseiva, 2008 .

Air Pollution Mapping Using Nonlinear Land Use Regression Models

Mikhail F. Kanevski, Alexandre Champendal, Pierre-Emmanuel Huguenot, 2014, ICCSA.

Extreme Learning Machines for spatial environmental data

Mikhail Kanevski, Michael Leuenberger, M. Kanevski, 2015, Comput. Geosci..

Analysis of Clustering and Unsupervised Learning of Geospatial Demographic Data

Mikhail Kanevski, Jean Golay, M. Kanevski, 2014 .

Snowmaking in ski resorts: spatial decision support for management of snowpack

M. Schumacher, M. Kanevski, M. Doctor, 2010 .

Feature selection using simple and efﬁcient machine learning models. Case studies and software tools

M. Kanevski, Fabian Guignard, Federico Amato, 2019 .

A Methodology for Automatic Analysis and Modeling of Spatial Environmental Data

M. Kanevski, 2013 .

Multitask Learning of Environmental Spatial Data

Mikhail Kanevski, M. Kanevski, 2012 .

Machine learning analysis and modeling of interest rate curves

Mikhail F. Kanevski, Vadim Timonin, M. Kanevski, 2010, ESANN.

A novel framework for spatio-temporal prediction of environmental data using deep learning

M. Kanevski, Fabian Guignard, Federico Amato, 2020, Scientific Reports.

Community detection analysis in wind speed-monitoring systems using mutual information-based complex network.

L. Telesca, M. Kanevski, Fabian Guignard, 2018, Chaos.

Validation of Logistic Regression Models for Landslide Susceptibility Maps

Mikhail F. Kanevski, J. Wang, Alexei Pozdnoukhov, 2009, 2009 WRI World Congress on Computer Science and Information Engineering.