Over the past few decades, application of simple statistical procedures with considerable heuristic or judgmental input was the beginning of forecasting, then in the 80’s, sophisticated time series models started to be used by some of the dynamic system operators, and these approaches, were to become pioneering works in this field.
Soft computing methods including support vectors regression (SVR), fuzzy inference system (FIS) and artificial neural networks (ANN) to time-series forecasting (TSF) has been growing rapidly in order to unify the field of forecasting and to bridge the gap between theory and practice, making forecasting useful and relevant for decision-making in many fields of the sciences.
The purpose of this session is to hold smaller, informal meetings where experts in a particular field of forecasting can discuss forecasting problems, research, and solutions in the field of automatic control. There is generally a nominal registration fee associated with attendance.
This session aims to debate in finding solutions for problems facing the field of forecasting. We wish to hear from people working in different research areas, practitioners, professionals and academicians involved in this problematic.
The session seeks to foster the presentation and discussion of innovative techniques, implementations and applications of different problems that are Forecasting involved, specially in real-world problems applied to control and automation.
Journal of Forecasting .
• Time Series Analysis
• Time Series Forecasting
• Evaluation of Forecasting Methods and Approaches
• Forecasting Applications in Business, Energy and Price Demand, Hydrology, etc.
• Impact of Uncertainty on Decision Making
• Seasonal Adjustment
• Multivariate Time Series Modelling and Forecasting
• Marketing Forecasting
• Economic and Econometric Forecasting
Dr.Cristian Rodriguez, the Guest Editor of the Special Issue on "Bayesian Time Series Forecasting" at the Journal of Forecasting and the organizer of the Special Session in ITISE-2022:
"SS2. Computational Intelligence for Applied Time Series Forecasting in Complex Systems (CIATSFCS)".
Prof. Cristian Rodriguez Rivero
,University of Amsterdam, email@example.com, IEEE CIS, Co-Founder LA-CIS.
Prof. Alvaro Orjuela Cañón
,Universidad del Rods, firstname.lastname@example.org, IEEE CIS, Co-Founder Board of Directors of LA-CIS.
Prof. Héctor Daniel Patiño
,Universidad Nacional de San Juan, Argentine,email@example.com. IEEE CIS.
Prof. Julián Antonio Pucheta
,Universidad Nacional de Córdoba, Argentine,firstname.lastname@example.org.
Prof. Gustavo Juarez
,Universidad Nacional de Tucumán, Argentine, email@example.com, IEEE CIS.
Prof. Leonardo Franco
,School of Engineering in Informatics, University of Malaga, Spain. firstname.lastname@example.org. IEEE CIS.