- This project is based on previous project of our group: https://github.com/chasebk/code_OCRO_MLNN
- The proposed model included:
- ELM network
- SLO/ISLO algorithm
- SLO/ISLO + ELM network
- data:
- app: include formatted data
- benchmark: results of benchmark functions
- utils: Helped functions such as IO, Draw, Math, Settings (for all model and parameters), Preprocessing...
- paper: include 2 main folders:
- results: forecasting results of all models (3 folders inside)
- final: final forecasting results (runs on server)
- stability: final stability results(runs on server)
- results: forecasting results of all models (3 folders inside)
- model: (4 folders)
- app: The code for application
- hybrid_cfnn: MHA + CFNN
- hybrid_elm: MHA + ELM
- hybrid_flnn: MHA + FLNN
- hybrid_mlp: MHA + MLP
- mha:
- draw_opposition: Draw the figure in opposition part in paper
- benchmark.py: The code for benchmark function
- COA.py: COA algorithm
- SLO.py: SLO and ISLO algorithm
- app: The code for application
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If you want to know more about code, or want a pdf of both above paper, contact me: nguyenthieu2102@gmail.com
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Take a look at this repos, the simplify code using python (numpy) for all algorithms above. (without neural networks)