/code_ISLO_ELM

A study on swarm intelligence optimizing neural networks for workload elasticity prediction

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A study on swarm intelligence optimizing neural networks for workload elasticity prediction

How to read my repository

  1. data:
    • app: include formatted data
    • benchmark: results of benchmark functions
  2. utils: Helped functions such as IO, Draw, Math, Settings (for all model and parameters), Preprocessing...
  3. 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)
  4. 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

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