ITISE 2022 : 8th International conference on Time Series and Forecasting
Call For Papers
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.
Submission of Special Session proposals: January 4th, 2022.
Submission of abstract or papers by authors: January 25th, 2022.
Notification of provisional acceptance: April 27th, 2022.
Early Registration: May 25th, 2022.
ITISE CONFERENCE: June 27th-30th, 2022.
Time Series Analysis and Forecasting
Nonparametric and functional methods
Probabilistic approaches to modeling macroeconomic uncertainties
Uncertainties in forecasting processes
Forecasting with Many Models. Model integration
Forecasting theory and adjustment
Forecasting performance evaluation
Data preprocessing methods: Data decomposition, seasonal adjustment, singular
spectrum analysis, detrending methods, etc.
Econometrics and Forecasting
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
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
Forecasting Complex/Big data
Forecasting in real problems
Atmospheric science forecasting
Modelling and forecasting in power markets
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).