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ENBIS-21 Online Conference

13–15 Sept 2021
Online
Europe/Berlin timezone

Session

Machine learning and industrial applications (SFdS)

PS51_IS5
14 Sept 2021, 16:45
Online

Online

Conveners

Machine learning and industrial applications (SFdS)

  • Chair: Yannig Goude (EDF R&D)

Description

Societe Francaise de Statistique (SFdS)

Presentation materials

There are no materials yet.

  1. 31. ShapKit: a Python module dedicated to local explanation of machine learning models
    Vincent Thouvenot
    14/09/2021, 16:45

    Machine Learning is enjoying an increasing success in many applications: defense, cyber security, etc. However, models are often very complex. This is problematic, especially for critical systems, because end-users need to fully understand the decisions of an algorithm (e.g. why an alert has been triggered or why a person has a high probability of cancer recurrence). One solution is to offer...

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  2. 32. Online Hierarchical Forecasting for Power Consumption Data
    Margaux Brégère
    14/09/2021, 17:05
    Other/special session/invited session

    We propose a three-step approach to forecasting time series of electricity consumption at different levels of household aggregation. These series are linked by hierarchical constraints -global consumption is the sum of regional consumption, for example. First, benchmark forecasts are generated for all series using generalized additive models; second, for each series, the aggregation algorithm...

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  3. 110. PHEBUS, a Python package for the probabilistic seismic Hazard Estimation through Bayesian Update of Source models
    Merlin Keller (EDF R&D, France)
    14/09/2021, 17:25
    Other/special session/invited session

    We propose a methodology for the selection and/or aggregation of probabilistic seismic hazard analysis (PSHA) models, which uses Bayes's theory by optimally exploiting all available observations, in this case, the seismic and accelerometric databases. When compared to the actual method of calculation, the proposed approach, simpler to implement, allows a significant reduction in computation...

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  4. 121. Generalized additive models for ensemble electricity demand forecasting
    Matteo Fasiolo
    14/09/2021, 17:45
    Other/special session/invited session

    Future grid management systems will coordinate distributed production and storage resources to manage, in a cost-effective fashion,
    the increased load and variability brought by the electrification of transportation and by a higher share of weather-dependent production.
    Electricity demand forecasts at a low level of aggregation will be key inputs for such systems. In this talk, I'll focus on...

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