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https://github.com/cvxgrp/smooth_multiperiodic_forecasting_experiments

Notebook accompanying numerical results section of the paper "Interpretable Net Load Forecasting Using Smooth Multiperiodic Features".

https://github.com/cvxgrp/smooth_multiperiodic_forecasting_experiments

Science Score: 26.0%

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    Low similarity (4.7%) to scientific vocabulary
Last synced: 11 months ago · JSON representation

Repository

Notebook accompanying numerical results section of the paper "Interpretable Net Load Forecasting Using Smooth Multiperiodic Features".

Basic Info
  • Host: GitHub
  • Owner: cvxgrp
  • Language: Jupyter Notebook
  • Default Branch: main
  • Size: 85.3 MB
Statistics
  • Stars: 3
  • Watchers: 2
  • Forks: 1
  • Open Issues: 1
  • Releases: 0
Created over 2 years ago · Last pushed over 1 year ago
Metadata Files
Readme

README.md

This directory contains a Jupyter notebook and 3 data files to reproduce the results of the paper Interpretable Net Load Forecasting Using Smooth Multiperiodic Features.
Used packages and their versions are:
| Package | Version | |----------------|----------| | pandas | 1.3.1 | | numpy | 1.21.2 | | cvxpy | 1.1.14 | | matplotlib | 3.4.2 | | math | Built-in | | time | Built-in | | scipy | 1.7.1 | | seaborn | 0.11.2 |

Owner

  • Name: Stanford University Convex Optimization Group
  • Login: cvxgrp
  • Kind: organization
  • Location: Stanford, CA

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  • keithbriggs (1)
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