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This project is the source code for the paperTime Series Forecasting based on High-Order Fuzzy Cognitive Maps and Wavelet Transform, which is now published inIEEE TFS.

• The fileWavelet_HFCM.py is the main program to perform forecasting time series by using Wavelet-HFCM.
• Defining the basic functions of an FCM,FCMs.py is used in the main program, and there is no need to run it seperately.
• The outcomes aboutthe effects of two hyper-parameters (the orderk and number of nodesNc）on Wavelet-HFCM are saved into the fileOutcome_for_papers/output_sunspot_sp500.xlsx, and their corresponding plots are saved into the directory./Outcome_for_papers/impact_parameters/ .

• python (3.6)
• matplotlib (3.0.3)
• seaborn (0.9.0)
• pandas (0.24.2)
• numpy (1.16.3)

Here is an example for MG-chaos data.

If you find this work useful, please cite our paper:

@article{yang2018time,  title={Time-series forecasting based on high-order fuzzy cognitive maps and wavelet transform},  author={Yang, Shanchao and Liu, Jing},  journal={IEEE Transactions on Fuzzy Systems},  volume={26},  number={6},  pages={3391--3402},  year={2018},  publisher={IEEE}}