Analyzing EEG Patterns in Functional Food Consumption: The Role of PCA in Decision-Making Processes

The impact of obesity and diabetes are two central reasons for the high rate of developing cardiovascular diseases in this country, which is largely due to their ultra-processed, diet-rich foods. Supervised Learning for Decision Making: A Case Study of Functional Food Taste Perceptions In this experiment, we trained ordinary consumers to estimate the taste preferences of a unique group from which no ratings were available(11) and established that decision making can be performed through supervision. A deep learning neural network architecture according to the present disclosure is designed to model the decision-making behavior of consumers consuming functional products. The efficiency of the model can be increased upto 1.23% making use of proper values for the rest of the hyperparameters as explained in experiments carried out where we set the optimal configuration so that nurturing it gives the best results.

@article{P´erez2024,
  title     = {Analyzing EEG Patterns in Functional Food Consumption: The Role of PCA in Decision-Making Processes},
  journal   = {International Journal of Advanced Computer Science and Applications},
  volume    = {15},
  number    = {11},
  year      = {2024},
  publisher = {The Science and Information Organization},
  author    = {Mauro Daniel Castillo P´erez and Jes´us Jaime Moreno Escobar and Ver´onica de Jes´us P´erez Franco and Ana Lilia Coria Pa´ez and Oswaldo Morales Matamoros},
  doi       = {10.14569/IJACSA.2024.01511119},
  url       = {https://doi.org/10.14569/IJACSA.2024.01511119}
}