Update README.md
Browse files
README.md
CHANGED
@@ -1,3 +1,42 @@
|
|
1 |
-
---
|
2 |
-
|
3 |
-
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
---
|
2 |
+
title: Transformer Model for Energy Consumption Prediction
|
3 |
+
description: >-
|
4 |
+
This model predicts energy consumption based on meteorological data and
|
5 |
+
historical usage.
|
6 |
+
license: gpl
|
7 |
+
---
|
8 |
+
# Transformer-Architecture for Energy Consumption Prediction
|
9 |
+
|
10 |
+
## Description
|
11 |
+
This model applies Transformer architecture to predict energy consumption over a 48-hour period using historical energy usage and weather data from 2021 to 2023.
|
12 |
+
|
13 |
+
## Model Details
|
14 |
+
**Model Type:** Transformer
|
15 |
+
**Data Period:** 2021-2023
|
16 |
+
**Variables Used:**
|
17 |
+
- `Lastgang`: Energy consumption data
|
18 |
+
- Weather variables
|
19 |
+
- Moving average and first difference of `Lastgang`
|
20 |
+
|
21 |
+
## Features
|
22 |
+
The model uses a sequence length of 192 (48 hours) to create input sequences for training and testing. Positional encodings are added to the sequences to provide temporal information to the Transformer model.
|
23 |
+
|
24 |
+
## Installation and Execution
|
25 |
+
To run this model, you need Python along with the following libraries:
|
26 |
+
- `pandas`
|
27 |
+
- `numpy`
|
28 |
+
- `matplotlib`
|
29 |
+
- `scikit-learn`
|
30 |
+
- `torch`
|
31 |
+
- `gputil`
|
32 |
+
- `psutil`
|
33 |
+
- `torchsummary`
|
34 |
+
|
35 |
+
### Steps to Execute the Model:
|
36 |
+
1. **Install Required Packages**
|
37 |
+
|
38 |
+
2. **Load your Data**
|
39 |
+
|
40 |
+
3. **Preprocess the data according to the specifications**
|
41 |
+
|
42 |
+
4. **Run the Script**
|