Papers by Alberto Guillen
Este trabajo plantea como principal objetivo exponer la problem´atica de las denominadas “FakeNew... more Este trabajo plantea como principal objetivo exponer la problem´atica de las denominadas “FakeNews” en los entornos educativos y propone una soluci´on software para diagnosticar y entrenar al alumnado. Este tipo de noticias corresponde generalmente a medios de comunicaci´on poco objetivos o creadores de contenidos que buscan ganar fama o repercusi´on; el problema es que se difunden a gran velocidad por la red, y gracias a la constante interacci´on en las redes sociales se han convertido en un serio problema contra el que luchar, especialmente en sectores de la poblaci´on con un criterio menos desarrollado. Partiendo del proyecto italiano #Bastabufale ideado por Laura Boldrini, propuesto por el Gobierno de Italia, se ha planteado el desarrollo de una plataforma software que permita entrenar al alumnado para ver si es capaz de identificar ”FakeNews”. Tambi´en permite recopilar m´etricas para poder evaluar la capacidad a nivel de individuo y a nivel de clase, siendo una herramienta fun...
Neurocomputing, Oct 1, 2007
There exists a wide range of paradigms, and a high number of different methodologies that are app... more There exists a wide range of paradigms, and a high number of different methodologies that are applied to the problem of time series prediction. Most of them are presented as a modified function approximation problem using input/output data, in which the input data are expanded using values of the series at previous steps. Thus, the model obtained normally predicts the value of the series at a time ðt þ hÞ using previous time steps ðt À t 1 Þ; ðt À t 2 Þ; . . . ; ðt À t n Þ. Nevertheless, learning a model for long term time series prediction might be seen as a more complicated task, since it might use its own outputs as inputs for long term prediction (recursive prediction). This paper presents the utility of two different methodologies, the TaSe fuzzy TSK model and the least-squares SVMs, to solve the problem of long term time series prediction using recursive prediction. This work also introduces some techniques that upgrade the performance of those advanced one-step-ahead models (and in general of any one-step-ahead model), where they are used recursively for long term time series prediction. r
Neurocomputing, 2007
This paper presents a novel learning methodology for multigrid-based fuzzy system (MGFS), and its... more This paper presents a novel learning methodology for multigrid-based fuzzy system (MGFS), and its application to the CATS time series prediction benchmark. The MGFS model keeps the advantages of the traditional grid-based fuzzy systems (GBFS), and overcomes the problem inherent to all GBFSs when dealing with high dimensional input data. Thus the MGFS model keeps interpretability, low computational cost and high generalization. A novel architecture selection algorithm for MGFSs that allows performing input variable selection is proposed. It identifies the sub-optimal architecture, according to a provided data set of input/output data. The architecture selection algorithm is completed with a structure identification procedure, used to obtain the optimal input space partitioning of the different sub-grids of the model. The complete algorithm is used to obtain the MGFS models for the CATS series prediction problem, solved using a direct prediction-based approach. r
La flora i la vegetació
La Universitat De Valencia I Els Seus Entorns L Horta De Valencia El Massis Del Caroig El Carrascal De La Font Roja I La Serra De Mariola 2014 Isbn 9788437094267 Pags 232 235, 2014
A new class of 16-ary Amplitude Phase Shift Keying (APSK) coded modulations deemed double-ring PS... more A new class of 16-ary Amplitude Phase Shift Keying (APSK) coded modulations deemed double-ring PSK modulations best suited for (satellite) nonlinear channels is proposed. Constellation parameters optimization has been based on geometric and information-theoretic considerations. Furthermore, pre-and post-compensation techniques to reduce the nonlinearity impact have been examined. Digital timing clock and carrier phase have been derived and analyzed for a Turbo coded version of the same new modulation scheme. Finally, the performance of state-of the art Turbo coded modulation for this new 16-ary digital modulation has been investigated and compared to the known TCM schemes. It is shown that for the same coding scheme, double-ring APSK modulation outperforms classical 16-QAM and 16-PSK over a typical satellite nonlinear channel due to its intrinsic robustness against the High Power Amplifier (HPA) nonlinear characteristics. The new modulation is shown to be power-and spectrally-efficient, with interesting applications to satellite communications.
Clustering-Based TSK neuro-fuzzy model for function approximation with interpretable sub-models
Proceedings of the 8th International Conference on Artificial Neural Networks Computational Intelligence and Bioinspired Systems, 2005
Abstract. TSK models are a very powerful tool for function approxima-tion problems given a datase... more Abstract. TSK models are a very powerful tool for function approxima-tion problems given a dataset of input/output data. Given a global error function to approximate, there are several methodologies for training (adjust the parameters and find the optimal structure) the TSK model. ...
Neurocomputing, Oct 1, 2009
The design of radial basis function neural networks (RBFNNs) still remains as a difficult task wh... more The design of radial basis function neural networks (RBFNNs) still remains as a difficult task when they are applied to classification or to regression problems. The difficulty arises when the parameters that define an RBFNN have to be set, these are: the number of RBFs, the position of their centers and the length of their radii. Another issue that has to be faced when applying these models to real world applications is to select the variables that the RBFNN will use as inputs. The literature presents several methodologies to perform these two tasks separately, however, due to the intrinsic parallelism of the genetic algorithms, a parallel implementation will allow the algorithm proposed in this paper to evolve solutions for both problems at the same time. The parallelization of the algorithm not only consists in the evolution of the two problems but in the specialization of the crossover and mutation operators in order to evolve the different elements to be optimized when designing RBFNNs. The subjacent genetic algorithm is the non-sorting dominated genetic algorithm II (NSGA-II) that helps to keep a balance between the size of the network and its approximation accuracy in order to avoid overfitted networks. Another of the novelties of the proposed algorithm is the incorporation of local search algorithms in three stages of the algorithm: initialization of the population, evolution of the individuals and final optimization of the Pareto front. The initialization of the individuals is performed hybridizing clustering techniques with the mutual information (MI) theory to select the input variables. As the experiments will show, the synergy of the different paradigms and techniques combined by the presented algorithm allow to obtain very accurate models using the most significant input variables.
Multiobjective RBFNNs Designer for Function Approximation: An Application for Mineral Reduction
Lecture Notes in Computer Science, 2006
Abstract. Radial Basis Function Neural Networks (RBFNNs) are well known because, among other appl... more Abstract. Radial Basis Function Neural Networks (RBFNNs) are well known because, among other applications, they present a good perfor-mance when approximating functions. The function approximation prob-lem arises in the construction of a control system to optimize the ...
Determining Marital Dissolutions Duration with Fuzzy Inference Systems
Marital dissolutions have many undesirable consequences for society, from the point of view of pu... more Marital dissolutions have many undesirable consequences for society, from the point of view of public health and given the increase in resources that have to be assigned to deal with them. With the introduction of divorce in Spain on June 22ed 1981, it has become possible ...
Radar Observations of Winds and Turbulence in the Stratosphere and Mesosphere
Journal of the Atmospheric Sciences, Feb 27, 1974
A technique for the observation of radar echoes from stratospheric and mesospheric heights has be... more A technique for the observation of radar echoes from stratospheric and mesospheric heights has been developed at the Jicamarca Radio Observatory. Signals are detected at the altitude ranges between 10-35 km and from 55-85 km with powers from many to several tens of decibels above noise level. The three most important frequency spectrum characteristics-power, Doppler shift and spectrum width-are observed in real time. The power levels as well as the spectral width are explained in terms of turbulent layers, with a thickness of the order of 100 m, in regions with a positive potential temperature or electron density vertical gradients. Continuous wind velocity records are obtained with a precision of the order of 0.02-0.2 m sec1 for the vertical component and 0.20-2 m sec1 for the horizontal, with a time resolution of the order of 1 min. The highest precisions are obtained at stratosphere heights. Fluctuations in velocity in the mesosphere are observed at the shortest gravity wave periods with amplitudes of the order of 1 m sec1 for the vertical component and of 10 m sec1 for the horizontal. Tidal components at these altitudes are not as large as predicted by theory. A technique to obtain the power, the Doppler shift, and the width of the frequency spectrum of the echo signals from only two points of the correlation function is described.
Applied Optics, Jan 20, 2010
Tooth bleaching is becoming increasingly popular among patients and dentists since it is a relati... more Tooth bleaching is becoming increasingly popular among patients and dentists since it is a relatively noninvasive approach for whitening and lightening teeth. Instruments and visual assessment with respect to commercial shade guides are currently used to evaluate tooth color. However, the association between these procedures is imprecise and the degree of color change after tooth bleaching is known to vary substantially between studies; there are currently no objective guidelines to predict the effectiveness of a tooth-bleaching treatment. We propose a new methodology based on fuzzy logic as a natural means of representing the imprecision present when modeling the color change produced by a toothbleaching treatment on the basis of a tooth's initial chromatic values. This system has the advantage of producing a set of interpretable fuzzy rules that can subsequently be used by scientists and dental practitioners. The fuzzy system obtained has the special characteristic whereby the rule antecedents correspond to prebleaching shades of the well-known Vita commercial shade guide. Additionally, the rule consequents directly correspond with the expected CIELAB postbleaching values for each Vita shade, thanks to a modification of the system's inference structure. Finally, the values of these postbleaching CIELAB coordinates have been associated with Vita shades by evaluating their respective membership functions, thereby approximating which posttreatment Vita shades are to be expected for each prebleaching shade.
CITATIONS 0 READS 37 6 authors, including: Some of the authors of this publication are also worki... more CITATIONS 0 READS 37 6 authors, including: Some of the authors of this publication are also working on these related projects: Filogeografía comparada de plantas representativas de la flora mediterránea. Datos de interés ecológico y forestal. View project Study and conservation of genus Phoenix diversity View project P. Pablo Ferrer-Gallego Generalitat Valenciana
Les plantes medicinals
La Universitat De Valencia I Els Seus Entorns L Horta De Valencia El Massis Del Caroig El Carrascal De La Font Roja I La Serra De Mariola 2014 Isbn 9788437094267 Pags 170 173, 2014
Using intelligent system for medical decision-making to magnetic resonance imaging
International Journal of High Performance Systems Architecture, 2008
The problem of selecting an adequate set of variables from a given data set of a sampled function... more The problem of selecting an adequate set of variables from a given data set of a sampled function, becomes crucial by the time of designing the model that will approximate it. Several approaches have been presented in the literature although recent studies showed how the Delta Test is a powerful tool to determine if a subset of variables is correct. This paper presents new methodologies based on the Delta Test such as Tabu Search, Genetic Algorithms and the hybridization of them, to determine a subset of variables which is representative of a function. The paper considers as well the scaling problem where a relevance value is assigned to each variable. The new algorithms were adapted to be run in parallel architectures so better performances could be obtained in a small amount of time, presenting great robustness and scalability.
The use of Radial Basis Function Neural Networks (RBFNNs) to solve functional approximation probl... more The use of Radial Basis Function Neural Networks (RBFNNs) to solve functional approximation problems has been addressed many times in the literature. When designing an RBFNN to approximate a function, the first step consists of the initialization of the centers of the RBFs. This initialization task is very important because the rest of the steps are based on the positions of the centers. Many clustering techniques have been applied for this purpose achieving good results although they were constrained to the clustering problem. The next step of the design of an RBFNN, which is also very important, is the initialization of the radii for each RBF. There are few heuristics that are used for this problem and none of them use the information provided by the output of the function, but only the centers or the input vectors positions are considered. In this paper, a new algorithm to initialize the centers and the radii of an RBFNN is proposed. This algorithm uses the perspective of activation grades for each neuron, placing the centers according to the output of the target function. The radii are initialized using the center's positions and their activation grades so the calculation of the radii also uses the information provided by the output of the target function. As the experiments show, the performance of the new algorithm outperforms other algorithms previously used for this problem.
The 2006 Ieee International Joint Conference on Neural Network Proceedings, 2006
Radial Basis Function Neural Networks (RBFNNs) have been applied to solve problems of classificat... more Radial Basis Function Neural Networks (RBFNNs) have been applied to solve problems of classification, function approximation and time series prediction. In the design of an RBFNN it is necessary to set the values for the positions of the centers and the radii for each RBF. In the literature it is usually performed an initialization step to set the positions of the centers and, once they are placed, the radii are calculated using a heuristic. In this paper, a new algorithm to set the value of those two parameters is presented. This new algorithm uses a supervised learning in such a way that the position of the centers will be constrained by the output of the function to be approximated. Since each center represents a neuron that is activated by the input vectors, the radii are initialized using the center's positions and their activation grades. In this way, the calculation of the radii is also influenced by the output of the target function, not like in other heuristics where only the positions of the centers or the input vectors are considered. As the experiments show, the new algorithm outperforms other algorithms previously used for this problem.
Tipificación y estatus taxonómico de Centaurea resupinata subsp. virens comb. et stat. nov. (sect. Willkommia Blanca, Asteraceae)
Computación de altas prestaciones y competencias transversales. Cuidando el entorno y aprendiendo a reciclar
Experiencias De Innovacion E Investigacion Educativa En El Nuevo Contexto Universitario 2011 Isbn 978 84 15 03190 1 Pags 775 782, 2011
... Localización: Experiencias de innovación e investigación educativa en el nuevo contexto unive... more ... Localización: Experiencias de innovación e investigación educativa en el nuevo contexto universitario / coord. por Javier Paricio Royo, Ana Isabel Allueva Pinilla, María del Carmen Agustín Lacruz, Fernando Cruz Bello, 2011, ISBN 978-84-15031-90-1 , págs. 775-782. ...
El meningioma en edad pedi�trica: Revisi�n de 10 casos
Neurocirugia, 2008
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Papers by Alberto Guillen