Subventions et des contributions :

Titre :
Predictive and visual analytics for strategic business planning
Numéro de l’entente :
EGP2
Valeur d'entente :
12 500,00 $
Date d'entente :
10 janv. 2018 -
Organisation :
Conseil de recherches en sciences naturelles et en génie du Canada
Location :
Saskatchewan, Autre, CA
Numéro de référence :
GC-2017-Q4-00736
Type d'entente :
subvention
Type de rapport :
Subventions et des contributions
Informations supplémentaires :

Subvention ou bourse octroyée s'appliquant à plus d'un exercice financier (2017-2018 à 2018-2019).

Nom légal du bénéficiaire :
Hamilton, Howard (University of Regina)
Programme :
Subvention d'engagement partenarial Plus pour les universités
But du programme :

Celero Solutions requires research on predictive and visual analytics for strategic business planning. A particular concern is making predictions about the Canadian economy and especially the business of Canadian credit unions.x000D
The main objectives of the research project are (1) to improve a predictive model of the Canadian credit union business that incorporates publicly available and private economic data concerning global, national, and local economic factors, and (2) to improve a dashboard that displays information about credit union health and performance in an easy to understand format. x000D
Given an initial model based on auto-regressive integrated moving averages (ARIMA), a wide variety of predictive analytics techniques including vector auto-regression (VAR), machine learning (classification learning and deep learning), and data mining will be evaluated to determine whether they improve predictive accuracy. The dashboard will be improved to display the input and summarized output for a large variety of data sources. Research will be performed to determine an appropriate way for the graphical user interface (GUI) to display alerts for cases where the actual economic and business performance significantly deviates from forecasts. This information will be given for individual credit unions and also presented in the context of aggregated values.x000D
In the evaluation part of the research, first the improved predictive model will be implemented and verified using some artificial data. Next, we will apply the improved model to historical data to determine its effectiveness. A variety of conditions will be simulated to ensure that alerts are produced. Separately, as part of the evaluation, we will perform detailed software testing on the dashboard to ensure that all required functionality is present and works correctly and reliability. Finally, the software prototype will be evaluated in association with Celero personnel in the context of performing strategic business planning for the next year.x000D
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