• Generalife Palace
  • Alhambra View
  • Alhambra's Night
  • Granada's Panoramic (I)
  • Granada's Panoramic (II)
  • Granada's Cathedral
  • Moorish Windows
  • Court of the Lions
  • Costa Tropical of Granada
Generalife Palace1 Alhambra View2 Alhambra's Night3 Granada's Panoramic (I)4 Granada's Panoramic (II)5 Granada's Cathedral6 Moorish Windows7 Court of the Lions8 Costa Tropical of Granada9
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Special Session Proposals


  • SS1 Forecasting Evolution



    Organizer:
    Prof. Philip Gerrish, School of Biology, Georgia Institute of Technology, 310 Ferst Dr, Atlanta, GA 30332
    SS2 Forecasting Climate –Weather and Operation Impact on Reliability, Safety and Resilience of Critical Infrastructures



    Organizers:
    Prof. Krzysztof Kołowrocki, Gdynia Maritime University, Poland
    Prof. Joanna Soszyńska-Budny, Gdynia Maritime University, Poland
    SS3 Applications of time series for hydro-climatic data



    Possible tutorial: Monte Carlo methods for goodness-of-fit tests (B. Remillard)

    Aim: The goal is to bring together theoreticians and practitioners interested in time series with applications to hydro-climatic data.

    The topics covered will include long-memory, notions of persistence, estimation problems, hidden Markov models, goodness-of-fit, and detection of change-points.

    Organizers:
    Prof. Bruno Remillardi, Professor at HEC Montréal. Consultant at the National Bank of Canada
    Prof. Bouchra R. Nasri
    SS4 Times series analysis in geosciences



    Motivation and objectives for the session.

    Times series are ubiquitous in geosciences. Time series analysis is amply used in hydrology, climatology, geology, environmental geosciences, geophysics, etc. The main objective of this session is the presentation of methodologies and cases studies dealing with the analysis of times series analysis in geosciences. New theoretical developments, new algorithms implementing known methodologies, new strategies for dealing with classical problems or classical methodologies dealing with new problems as well as case studies are appropriate for this special session.

    Organizers:
    Prof. Eulogio Pardo-Igúzquiza, Professor at Instituto Geológico y Minero de España (IGME)
    Prof. Francisco Javier Rodríguez-Tovar, Depart. Estratigrafía y Paleontología, University of Granada, Spain.
    SS5 Forecasting in High Dimension and Complex/Big Data



    Forecasting high-dimensional data and analysis of time series with hundreds/thousand of attributesinations) is challenging problem, with application in multiple problems of real life (problems in economy, energy, climate, etc).

    Real problems in which you have to predict / analyze or treat large volumes of data are welcome to this session.

    Organizer:
    Prof. Dr. Luis Javier Herrera , Dep. Computer Architecture and Computer Technology, University of Granada, Spain
    Prof. Dr. Ignacio Rojas , Dep. Computer Architecture and Computer Technology, University of Granada, Spain
    SS6 Quantum Computing



    The European Community initiated in February 2016 the QuantumManifesto (http://qurope.eu/manifesto) a €1 billion Flagship-scale Initiative in Quantum Technology to bridge the gap between research and application. We invite mathematicians and engineers to contribute to this program. The objective of this special session is to inform about the current status of quantum computing, related algorithm problems, actual known applications, and the need for further emerging markets to boost this technology.

    Organizers:
    Prof. Peter Gloesekoetter, Fachbereich Elektrotechnik und Informatik, Stegerwaldstraße 39, 48565 Steinfurt, Germany.
    Dr. Bernd Burchard, Elmos Semiconductor AG, Germany.
    SS7 Computational Intelligence methods for Time Series

    Within the field of science and engineering, it is very common to have data arranged in the form of time series data which must be subsequently analyzed, modeled and classified with the eventual goal of predicting future values. The literature shows that all these tasks related to time series can be undertaken using computational intelligence methods. In fact, new and further computational intelligence approaches, their efficiency and their comparison to statistical methods and other fact-checked computational intelligence methods, is a significant topic in academic and professional projects and works.

    Therefore, this special session aims at showing to our research community high quality and state of the art computational intelligence (and statistical) related works, applied to time series data and their tasks: analysis, forecasting, classification, and clustering. Furthermore, the experts can, from the starting point that the works shown provide, discuss different solutions and research issues for these topics.

    The topics of interest include but are not limited to:

    Computational Intelligence (CI) techniques applied to

    • time series analysis
    • time series modeling
    • time series forecasting
    • time series classification
    • time series clustering
    • statistical and CI techniques for time series, comparative evaluation and/or novel propositions
    • Organizer:
      Prof. Dr. Héctor Pomares , Dep. Computer Architecture and Computer Technology, University of Granada, Spain
      Prof. Dr. German Gutierrez , Dep. Computer Science, E.P.S. University Carlos III of Madrid, Spain
    SS8 Structural Time Series Models

    SS9 Recent Developments on Time-Series Modelling.

    SS10 Expert Systems with Time Series - Data

    This session is to present systems which deals with making a decision based on time-series data.

    Session aims to bring into existence recent and becoming developments in computational mathematics that could be used in the field of time series data with expert systems. Papers that concentrate on future developments are especially welcome.

    The topics of interest include but are not limited to:

    • Computational logic applied to the expert systems with time series data e.g. similarities etc.
    • New methods in neural networks applied to expert systems with time series e.g. LSTM etc.
    • Decision making based on time series data
    • Traffic control systems
    • Medical expert systems
    • Organizer:
      Prof. Dr. Kalle Saastamoinen , Department of Military Technology, National Defence University,Helsinki, Finland
    SS11 Spatio-temporal brain dynamics in attention tasks

    This session is devoted to presenting the latest research on analysis time series techniques and forecasting for spatio-temporal dynamics of oscillations of neural brain activity, measured by multi-electrode and functional magnetic resonance imaging recordings. We look for approaches dealing with non-stationarities in EEG signals through time and/or space domains, as well as facilitating their use in human-computer interaction. The scope includes a wide variety of applications of dynamic neuroimaging of brain function, among others, the following: The use of signal processing tools such as time-domain analysis, power spectral estimation, and wavelet transform in tasks involving electroencephalography (EEG) signals with a large number of channels, encouraging efficient channel selection metrics to measure the spatial relevance from one application to another. Extraction of informative features, aiming to take into account the relationships among EEG sensor/source signals in the form of brain connectivity as an efficient tool in neuroscience tasks. Development of strategic approaches to deal with the high variations of performance across and even within subjects, which may contribute to improving the reliability of human-computer interaction technology.

    Research contributions should be related but are not limited to one or more of the following topics:

    • Space and time information processing techniques for EEG activity in attention tasks
    • Spatiotemporal beamforming and Constrained methods for source reconstruction and localization
    • Machine learning identification of spatio-temporal EEG features
    • Spatiotemporal brain imaging data modeling (fMRI, EEG, MEG, fNIRS, etc.)
    • Spatio-Temporal Modeling of EEG Data for brain functioning and Understanding cognitive tasks
    • Brain connectivity networks analysis
    • Organizers:
      Prof. Dr. Juan Manuel Górriz , University of Granada, Spain.
      Prof. Dr. Pedro A. Valdes-Sosa , Cuban Neurosciences Center.
      Prof. Dr. César Germán Castellanos Dominguez , Universidad Nacional de Colombia