copper_price_forecast

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copper_price_forecast

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copper price(time series) prediction using bpnn and lstm

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- __init__.py
- const.py
- data_exploration.py
- data_loading.py
- model_evaluation.py
- model_visualization.py
- - __init__.py
  - co_lstm_predict_day.py
  - co_lstm_predict_sequence.py
- - __init__.py
  - co.csv
  - lstm.py
  - sin.csv
  - stock.csv
- - __init__.py
  - comparison_of_activation_function.md
- __init__.py
- __init__.py
- feature_engineering.py
- train_and_predict_mlp.py
- __init__.py
- correlation_analysis.py
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LICENSE
README.md

// repository documentation

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# Copper price forecast

This is an open source project aims at making a prediction of copper price using machine learning / deep learning approach. The language of this project is Python and the ideas may extend to other time series prediction problems as you like.

# Motivation

The motivation of launching this project is that copper is a kind of important raw material of some midstream and downstream materials, whose price is of great relevance to copper price. Thus a high accuracy of copper price prediction can to some extent providing purchasing decisions for the purchasing agent.

Here is a comparison of the fluctuation of the price of cooper and a kind of downstream material:

![image](https://github.com/liyinwei/res/raw/master/2017/copper_price_readme_1.png)

# Prerequisites

- [Python](https://www.python.org/) 3.5 + 
- [numpy](http://www.numpy.org/) 1.13.0 + 
- [pandas](http://pandas.pydata.org/) 0.20.2 + 
- [scikit-learn](http://scikit-learn.org/stable/) 0.18.1 + 
- [Keras](https://keras.io/) 2.0.4 + 
- [tensorflow](https://www.tensorflow.org/) 1.1.0 + 
- [matplotlib](http://matplotlib.org/) 2.0.2 +
- [mysql-connector-python-rf](https://pypi.python.org/pypi/mysql-connector-python-rf) 2.2.2 +

# Structure
- [common](https://github.com/liyinwei/copper_price_forecast/tree/master/common): common method such as data loading, model evaluation & model visualization etc.
- [mlp](https://github.com/liyinwei/copper_price_forecast/tree/master/mlp): predict copper price using sklearn.neural_network.MLPRegressor
- [lstm](https://github.com/liyinwei/copper_price_forecast/tree/master/lstm): predict copper price using keras.layers.recurrent.LSTM
- [pcb](https://github.com/liyinwei/copper_price_forecast/tree/master/pcb): correlation analysis of copper and a downstream material price

# Data
You can visit the [spiders project](https://github.com/liyinwei/spiders) and run [shfe](https://github.com/liyinwei/spiders/tree/master/shfe) to crawling copper future price from [Shanghai Futures Exchange](http://www.shfe.com.cn/).

# Running
There is a main method in each python file so you can run it easily.

the following is a sample of predict result of the [mlp](https://github.com/liyinwei/copper_price_forecast/tree/master/mlp) method:

![image](https://github.com/liyinwei/res/raw/master/2017/copper_price_readme_2.png)

while the following is a sample of predict result of the [lstm](https://github.com/liyinwei/copper_price_forecast/tree/master/lstm) method with epochs=500:

![image](https://github.com/liyinwei/res/raw/master/2017/copper_price_readme_3.png)

# Authors
- [Yinwei Li](https://github.com/liyinwei)
  - **wechat**: coridc
  - **email**: 251469031@qq.com

*Don't hesitate to contact me on any topics about this project at your convenience.*

# Contributors
- [Yinwei Li](https://github.com/liyinwei)

# Contributing

When contributing to this repository, you can first discuss the change you wish to make via issue, email, or any other method with the owners of this repository.

# License

This project is licensed under the [GNU General Public License v3.0](http://www.gnu.org/licenses/gpl-3.0.html) License - see the [LICENSE](https://github.com/liyinwei/copper_price_forecast/blob/master/LICENSE) file for details.

# Acknowledgments

I'd like hat tip to anyone who use the codes or send me any proposals of the project.

copper_price_forecast

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