Deep Learning Applied to Energy Forecast: Implementation and Evaluation

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As big data becomes a center for computing and modelling, tools for data analytics are most important for the**rapid development areas of artificial intelligent and machine learning. With the support of an NSERC Engage**project last year, we have developed a computational model for energy consumption forecasting and its**prediction uncertainty by applying the deep learning techniques of Artificial Neural Network. As next step, the**Engage Plus project aims to implement and evaluate the newly developed system model. We will also**investigate current advances in the alternative machine learning algorithms that have been used by the large**companies like Google and Microsoft.**The success of this project will benefit the industry partner by helping the company to adopt new innovate**technology and upgrade its current services. The work will contribute to the Canadian leadership in the creation**of artificial intelligence technology and enriches the economic growth.