… Six classification datasets and six prediction datasets are adopted to … learning algorithms
in the experiments. In the first part, all models are implemented for six benchmark classification …

… The interactions among attributes can also be observed in its dendritic neurons. … Todo,
“Approximate logic neuron model trained by states of matter search algorithm,” Knowl.Based Syst.…

… this study, a neuron model with dendrite morphology called LDNM is proposed to solve
high-dimensional classification … This operation approximates a logical OR operation in the binary …

… θi,j and approximates 0 otherwise. In … dendrites and epochs to realize sufficient learning.
From these results, we conclude that the proposed DNN can solve multiclass classification …

… classification problems, empirical evidence also validates the AISDNM can delete superfluous
synapses and dendrites to simplify its neural … be obtained to approximate the function of …

… as 0, the following equation can be approximated: … algorithm and dendrite neuron model
effectively, and DNM + BBO is established in this study, especially as a powerful algorithm to …

… In this study, a novel non-BP learning algorithm based on the differential evolution algorithm
is … best one for all tested fourteen classification, approximation and prediction problems. The …

… an evolutionary dendritic neuron model (EDNM) is proposed to solve classification problems…
Todo, “An approximate logic neuron model with a dendritic structure,” Neurocomputing, vol. …

… branch can be approximated as logic operation. In recent years, several dendritic computing
models … Five realistic classifications problems are considered in our research to validate our …

… it to large-scale classification problems. To achieve better … , an approximate Newton-type
method-neural network with random weights for the comparison; and three learning algorithms …