Influence of hidden neuron number on the performance of ANN models applied to deinking flotation data

CC-BY-NC-NDBalanović, KatarinaTrumić, MajaGavrilović, Tamara2025-12-122025-12-122025978-86-6305-164-510.5937/IOC25229Bhttps://ioc.tfbor.bg.ac.rs/public/2025/Proceedings_IOC_2025.pdfhttps://repozitorijum.tfbor.bg.ac.rs/handle/123456789/6053In this paper, the influence of the optimal number of neurons in an artificial neural network model, applied to data obtained from deinking flotation is presented and analyzed. The results indicate that when a wellperforming model is selected, it is not necessary to search for the optimal number of hidden neurons. However, when the applied model does not yield satisfactory results, determining the optimal number of neurons becomes essential.enArtificial neural networksHidden neuronsFlotationDeinkingInfluence of hidden neuron number on the performance of ANN models applied to deinking flotation dataconferenceObject