Deep-learning approaches for weather-dependent businesses
Deep learning techniques can enhance and improve weather forecasting and help weather-dependent businesses to encounter the effects of weather proactively.
But how does it work and how can it help solve today’s business challenges?
Topics discussed
- Deep neural networks and probabilistic approaches applied to solar forecasting
- The use of deep learning techniques to assess the impact of weather across major businesses
After the Webinar you’ll have an understanding of:
- Why deep learning can enhance weather forecasts for solar energy in comparison to the use of physical models and image processing technology
- How deep learning works
- A use case from PV production forecasting
- Why weather-dependent businesses should consider machine-learning technology for weather forecasts
- Biased data and the importance of a good data set
- The wide range of applications of weather decision-making engines
Chairman : Lionel Cordesses, Director – Intelligent Systems & Communications at IRT Saint Exupéry
Speakers : Pierre Aillaud, R&D Engineer at Reuniwatt and Johan Mathé, Co-founder & CEO atAtmo