Durán-Rosal, Antonio Manuel

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Durán-Rosal, Antonio Manuel

Información Personal
Posición:	Becario
Áreas de investigación:	Sin Categoría

Localización:	Rabanales
Publicaciones
A memetic dynamic coral reef optimisation algorithm for simultaneous training, design, and optimisation of artificial neural networks Boosting ridge for the extreme learning machine globally optimised for classification and regression problems Machine Learning Applications in Real-World Time Series Problems Gramian Angular and Markov Transition Fields applied to Time Series Ordinal Classification A multi-class classification model with parametrized target outputs for randomized-based feedforward neural networks Generalised Triangular Distributions for ordinal deep learning: novel proposal and optimisation An Evolutionary Artificial Neural Network approach for spatio-temporal wave height time series reconstruction A mixed distribution to fix the threshold for Peak-Over-Threshold wave height estimation Gamifying the classroom for the acquisition of skills associated with Machine Learning: a two-year case study Time series clustering based on the characterisation of segment typologies Potenciando el perfil profesional Científico de Datos mediante dinámicas de competición A new approach for optimal offline time-series segmentation with error bound guarantee Ordinal classification of the affectation level of 3D-images in Parkinson diseases Evolutionary artificial neural networks for accurate solar radiation prediction A new approach for optimal time-series segmentation A hybrid dynamic exploitation barebones particle swarm optimisation algorithm for time series segmentation Dynamical Memetization in Coral Reef Optimization Algorithms for Optimal Time Series Approximation Time series data mining: preprocessing, analysis, segmentation and prediction. Applications On the use of evolutionary time series analysis for segmenting paleoclimate data Efficient Fog Prediction with Multi-objective Evolutionary Neural Networks Simultaneous optimisation of clustering quality and approximation error for time series segmentation A statistically-driven Coral Reef Optimization algorithm for optimal size reduction of time series Detección y predicción de segmentos de altura de olas extremas Time series clustering based on the characterisation of segment typologies Detection of early warning signals in paleoclimate data using a genetic time series segmentation algorithm Distribution-Based Discretisation and Ordinal Classification Applied to Wave Height Prediction An Empirical Validation of a New Memetic CRO Algorithm for the Approximation of Time Series Hybrid Weighted Barebones Exploiting Particle Swarm Optimization Algorithm for Time Series Representation Identifying market behaviours using European Stock Index time series by a hybrid segmentation algorithm Detection and prediction of segments containing extreme significant wave heights Identification of extreme wave heights with an evolutionary algorithm in combination with a likelihood-based segmentation Multiobjective time series segmentation by improving clustering quality and reducing approximation error A coral reef optimization algorithm for wave height time series segmentation problems Clustering de Series Temporales basado en la Extracción de Tipologías de Segmentos Massive missing data reconstruction in ocean buoys with evolutionary product unit neural networks Hybridization of neural network models for the prediction of extreme significant wave height segments Multiclass Prediction of Wind Power Ramp Events Combining Reservoir Computing and Support Vector Machines On the Use of the Beta Distribution for a Hybrid Time Series Segmentation Algorithm Time Series Representation by a Novel Hybrid Segmentation Algorithm Detection of early warning signals in paleoclimate data using a genetic time series segmentation algorithm Applying a Hybrid Algorithm to the Segmentation of the Spanish Stock Market Index Time Series [Ver Menos]
Proyectos
Clasificación ordinal basada en aprendizaje profundo y neuro-evolución (ORCA-DEEP) Métodos de Aprendizaje Profundo en clasificación ORDINAL (MAP-ORDINAL) Aprendizaje dinámico de modelos de curvas de infectados y de número de camas hospitalarias y camas UCI ocupadas por COVID-19 en Andalucía mediante técnicas estadísticas y de Inteligencia Artificial Modelos de Aprendizaje de Máquina para la determinación óptima de la Supervivencia y la Asignación Donante/REceptor en trasplante hepático. MASS-ALLOCATION Aprendizaje del reconocimiento de emociones en personas con espectro autista. [Ver Todos]