Energy Forecasting with MATLAB

Event Type Start Time End Time
Webex 20 Oct 2020 - 14:00 BST 20 Oct 2020 - 15:30 BST

Overview

Time Title

14.00

Energy Forecasting with MATLAB

This session will demonstrate multiple modelling approaches for energy price forecasting with MATLAB.

15.00

Q&A and wrap-up

Agenda

This session demonstrates multiple modelling approaches for energy price forecasting with MATLAB.

Come along to find out how MATLAB can help with:

  • Using timetables to organize and manage data
  • Defining additional predictor variables to improve model quality
  • Fitting classical statistical models such as linear regression
  • Building machine learning models for time-series forecasting
  • Interpreting and explaining machine learning models via predictor analysis
  • Designing and training neural networks for time-series forecasting
  • Creating econometric models for time series such as ARIMA and GARCH
  • Assessing model quality using goodness-of-fit metrics

Who Should Attend

This session is intended for analysts, modellers, data scientists and financial professionals who have an interest in energy price and load forecasting. The content should also be of interest to those who perform other types of time-series modelling and forecasting.

About the Presenters

Ken Deeley

Ken Deeley is a member of the UK Engineering Team at MathWorks, specializing in data analytics and application development. He has 9 years of experience as a customer-facing engineer at MathWorks, helping users from a diverse range of industry applications. Before joining MathWorks, Ken completed a Master’s and PhD in mathematics.

Panos Brezas

Panos Brezas is a member of the UK Engineering Team at MathWorks, specializing in data analytics and control systems. He has experience in the financial and automotive industries. His academic background includes a Bachelor/Masters in Electrical Engineering and a PhD in control theory. 

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