Dr. François Anctil, Université Laval
The goal of this project is to evaluate if mesoscale (35 km) meteorological ensemble forecasts coupled to a short-range hydrological forecasting system can lead to improved forecasts, and thus help maximize hydropower production and minimize flood risks. Positive results would pave the way for a full project which would aim to design an efficient short-range hydrological ensemble forecasting system adapted to the climate and hydrology of the Great-Lakes and Saint Lawrence River basin.
[url=mailto:email@example.com]Dr. Jean-Marie Dufour[/url] , Université de Montréal
This project deals with the mathematics of risk modeling and resource management. Using mathematical and statistical methods, the team develops new tools to help the financial services industry make better decisions about when to trade and at what price based on the available financial data. During the past year, the team focused on the development of statistical methods for measuring volatility and assessing asset pricing models in financial markets.
[url=http://www.lacaisse.com/]Caisse de dépôt et placement du Québec[/url]
Dr. Irène Abi-Zeid , Université Laval
Dr. François Soumis, (École Polytechnique de Montréal)
Dr. Kim McAuley, Queen's University
Engineers use mathematical models to describe the production of plastics and other chemicals. The models contain unknown parameters that are estimated from plant data. In the past year, the research team analyzed several criteria that modelers use to decide how complex or how simplified their models should be. They showed that one popular model-selection criterion, the corrected Akaike Information Criterion, tends to select very simple models, and that another, the adjusted coefficient of determination, tends to select models with many parameters.
Dr. Paul Myers , University of Alberta
Dr. Bernard Gendron , Université of Montréal
Dr. Fahima Nekka , Université de Montréal