/MBTA_MATLAB_ML

Boston train station passenger flow number prediction - (BP Neural Network + Genetic Algorithm)

Primary LanguageJupyter NotebookApache License 2.0Apache-2.0

Boston Train Station's Passenger Flow Prediction

Using Genetic Algorithm to optimize BP Neural Network's initial weight and threshold value.

Two kind prediction: Whole Day prediction and Time Period Prediction.

Description

  • Data Pre-Processing.ipynb: Generating input and output csv files

  • MBTA_MATLAB Folder: Running in MATLAB to do prediction

Tools

  • Neural Network Training Toolbox

  • Sheffield Genetic Algorithms Toolbox

  • MatLab

  • Python Jupyter

  • Numpy / Pandas

  • Matplot

  • Sklearn

Data

  • MBTA historical passenger flow data, available in MBTA.

  • Weather (Rain, Snow, Temperature) historical data, has been uploaded in current folder.

  • US Holiday Data, Week, Month...

Input

Output

Design Structure

  • Setting up BP Neural Network structure

  • Using GA optimize initial weight and threshold

  • Training and Testing BP Neural Network

BP Neural Network Structure

Genetic Algorithm Parameters

Outcomes Display

BP NN Prediction without GA && BP NN Prediction with GA

BP NN & BP NN + GA Comparison

Prediction Error - BP NN without GA

Prediction Error - BP NN with GA

Evaluation / Performance / Training State / Error Histogram