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2019 International Conference on Time Series and Forecasting (ITISE-2019)

The ITISE 2019 seeks to provide a discussion forum for scientists, engineers, educators and students about the latest ideas and realizations in the foundations, theory, models and applications for interdisciplinary and multidisciplinary research encompassing disciplines of computer science, mathematics, statistics, forecaster, econometric, etc, in the field of time series analysis and forecasting. The aims of ITISE 2019 is to create a a friendly environment that could lead to the establishment or strengthening of scientific collaborations and exchanges among attendees, and therefore, ITISE 2019 solicits high-quality original research papers (including significant work-in-progress) on any aspect time series analysis and forecasting, in order to motivating the generation, and use of knowledge and new computational techniques and methods on forecasting in a wide range of fields. Sponsored by the IEEE Computational Intelligence Society and other organizations.
When 25 September 2019 11:15 AM to
27 September 2019 11:15 AM
Where Granada ES
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1.- Time Series Analysis and Forecasting:

  • Nonparametric and functional methods
  • Vector processes
  • Probabilistic approaches to modeling macroeconomic uncertainties
  • Uncertainties in forecasting processes
  • Nonstationarity
  • Forecasting with Many Models. Model integration
  • Forecasting theory and adjustment
  • Ensemble forecasting
  • Forecasting performance evaluation
  • Interval forecasting
  • Data preprocessing methods: Data decomposition, seasonal adjustment, singular spectrum analysis, detrending methods, etc.

2.- Econometric and Forecasting:

  • Econometric models
  • Econometric Forecasting
  • Real time macroeconomic monitoring and forecasting
  • Advanced econometric methods

 

3.- Advanced methods and on-line learning in time series:

  • Adaptivity for stochastic models
  • On-line machine learning for forecasting
  • Aggregation of predictors
  • Hierarchical forecasting
  • Forecasting with computational intelligence
  • Time series analysis with computational intelligence
  • Integration of system dynamics and forecasting models

4.- High Dimensional and Complex/Big Data

  • Local vs global forecasts
  • Dimension reduction techniques
  • Multiscaling
  • Forecasting Complex/Big data

5.- Forecasting in real problems:

  • Health forecasting
  • Atmospheric science forecasting
  • Telecommunication forecasting
  • Hydrological forecasting
  • Traffic forecasting
  • Tourism forecasting
  • Marketing forecasting
  • Modelling and forecasting in power markets
  • Energy forecasting
  • Climate forecasting
  • Financial forecasting and risk analysis
  • Forecasting electricity load and prices
  • Forecasting and planning systems
  • Applications in real problem (finance, transportation, networks, meteorology, ehealth, environment, etc).

  

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