Retrospective on Neural Networks
Neural Network models gained popularity in energy forecasting in the 1990’s. Unlike regression methods, neural networks are capable of estimating the shape of nonlinear relationships and the strength of interactions among variables. In this Brown Bag, we dig into this capability, compare the predictive power of neural networks to a list of regression methods and decision tree methods, and show how neural network derivatives can be used as a feature engineering tool for structured regression models.
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This is the 2nd free forecasting brown bag webinar of 2024. Click below to register and read detailed descriptions for each the 2024 topics listed below on the Webinars tab.
- The Ins and Outs of Net Load Forecasting at the Edge
- Retrospective on Neural Networks
- Integrating Building Electrification Impacts into Long-term Load Forecasts
- 2024 Forecast Accuracy Benchmarking Survey & Energy Trends – Survey Participants Only*
Participation is free, but prior registration is required. Each webinar lasts approximately one hour, allowing 45 minutes for the presentation and 15 minutes for questions. Webinars typically start at noon Pacific time. If you can’t attend a webinar or missed one, don’t worry! Your registration gives you access to recordings.
*attendance restricted to survey participants