The ITISE 2022 (8th International conference on Time Series and Forecasting) 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 2022 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 2022 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.


IMPORTANT DATES

Submission of Special Session proposals: February 19th, 2022.
Submission of abstract or papers by authors: March 6th, 2022.
Notification of provisional acceptance: May 5th, 2022.
Early Registration: May 15th, 2022.
ITISE CONFERENCE: June 27th-30th, 2022.



Conference Topics
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.
Econometrics and Forecasting
Econometric models
Economic and econometric forecasting
Real macroeconomic monitoring and forecasting
Advanced econometric methods
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

High Dimension and Complex/Big Data
Local versus global forecasts
Dimension reduction techniques
Multiscaling
Forecasting Complex/Big data
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).