Utilização de redes neurais artificiais para classificação de farinha de trigo em uma indústria de biscoitos e massas - Spancerski, Jandrei Sartori (2020)
Currently, the highly competitive environment requires food companies to optimize their processes. In this context, this work aims to classify, using artificial neural networks, wheat flour from a biscuit and pasta industry. The database, made available by the company, presents 7666 observations. A classification model, based on MLP Neural Networks (Multilayer Perceptron), was implemented in the Python language. To determine the hyperparameters of the neural network, 11664 models were tested. From the results obtained, it was observed that the model with the optimized hyperparameters presents in the classification of wheat flour, an accuracy greater than 95%.