Towards a Quantum based GA Search for an Optimal Artificial Neural Networks Architecture and Feature Selection to Model NOx Emissions: A Case Study

Mazen A. R. Azzam, Joseph Zeaiter, Mariette Awad. Towards a Quantum based GA Search for an Optimal Artificial Neural Networks Architecture and Feature Selection to Model NOx Emissions: A Case Study. In IEEE Congress on Evolutionary Computation, CEC 2020, Glasgow, United Kingdom, July 19-24, 2020. pages 1-8, IEEE, 2020. [doi]

@inproceedings{AzzamZA20,
  title = {Towards a Quantum based GA Search for an Optimal Artificial Neural Networks Architecture and Feature Selection to Model NOx Emissions: A Case Study},
  author = {Mazen A. R. Azzam and Joseph Zeaiter and Mariette Awad},
  year = {2020},
  doi = {10.1109/CEC48606.2020.9185508},
  url = {https://doi.org/10.1109/CEC48606.2020.9185508},
  researchr = {https://researchr.org/publication/AzzamZA20},
  cites = {0},
  citedby = {0},
  pages = {1-8},
  booktitle = {IEEE Congress on Evolutionary Computation, CEC 2020, Glasgow, United Kingdom, July 19-24, 2020},
  publisher = {IEEE},
  isbn = {978-1-7281-6929-3},
}