Iván Machón-González

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The self-organizing map (SOM) is a suitable algorithm for data visualization but its topological preservation makes the vector quantization non-optimal. This paper aims to improve the lack of quantization precision in the SOM. An energy cost function based on two different kernels is formulated to obtain a batch algorithm. A bivariate normal distribution is(More)
Numerous papers related to the estimation of wastewater parameters have used artificial neural networks. Although successful results have been reported, different problems have arisen such as overtraining, local minima and model instability. In this paper, two types of neural networks, feed-forward and neural gas, are trained to obtain a model that(More)
There are several successful approaches dealing with imbalanced datasets. In this paper, the Fuzzy Labeled Neural Gas (FLNG) is extended to work with this type of data. The proposed approach is based on assigning two different values in the learning rate depending on the data vector membership of the class. The technique is tested with several datasets and(More)
SOM-NG is a hybrid algorithm that is able to carry out visualization of process data, nonlinear function approximation, classification and clustering. The supervised version of SOM-NG produces a new type of 2D lattices called gradient planes which are useful to determine the dynamics of a target variable according to the remaining training variables. In(More)
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