metadata

title: LSTM Model for Energy Consumption Prediction
description: >-
  This model predicts energy consumption based on meteorological data and
  historical usage.
license: gpl

LSTM for Energy Consumption Prediction

Description

This model applies Long Short-Term Memory (LSTM) architecture to predict energy consumption over a 48-hour period using historical energy usage and weather data from 2021 to 2023.

Model Details

Model Type: LSTM
Data Period: 2021-2023
Variables Used:

LSTM with Energy consumption data and weather data
LSTM with Energy consumption data and two additional variables: 'Lastgang_Moving_Average' and 'Lastgang_First_Difference'

Features

The model uses a sequence length of 192 (48 hours) to create input sequences for training and testing.

Installation and Execution

To run this model, you need Python along with the following libraries:

pandas
numpy
matplotlib
scikit-learn
torch
gputil
psutil
torchsummary

Steps to Execute the Model:

Install Required Packages
Load Your Data
Preprocess the Data According to the Specifications
Run the Script