Dorado-Moreno, Manuel

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Dorado-Moreno, Manuel

Personal Information
Position:	Doctorando FPU
Research areas:	Uncategorized

Location:	Campus de Rabanales, edificio Albert Einstein, 3ª Planta, Ala Sur, CP: 14071
Publications
Building Suitable Datasets for Soft Computing and Machine Learning Techniques from Meteorological Data Integration: A Case Study for Predicting Significant Wave Height and Energy Flux Ordinal multi-class architecture for predicting wind power ramp events based on reservoir computing Multi-task learning for the prediction of wind power ramp events with deep neural networks Predicción ordinal de rampas de viento usando Echo State Networks de complejidad reducida Predicción ordinal de rampas de viento usando Echo State Networks de complejidad reducida Wind power ramp events ordinal prediction using minimum complexity echo state networks Robust estimation of wind power ramp events with reservoir computing Identification of extreme wave heights with an evolutionary algorithm in combination with a likelihood-based segmentation Dynamically weighted Evolutionary Ordinal Neural Network for solving an Imbalanced Liver Transplantation Problem Combining Reservoir Computing and Over-Sampling for Ordinal Wind Power Ramp Prediction From outside to hyper-globalisation: an Artificial Neural Network ordinal classifier to measure the extent of globalisation 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 Ordinal Evolutionary Artificial Neural Networks for Solving an Imbalanced Liver Transplantation Problem Classification of goat genetic resources using morphological traits. Comparison of machine learning techniques with linear discriminant analysis Overcoming the linearity of Ordinal Logistic Regression adding non-linear covariates from Evolutionary Hybrid Neural Network models Nonlinear Ordinal Logistic Regression using covariates obtained by Radial Basis Function neural networks models Rating the Rich: An Ordinal Classification to Determine Which Rich Countries are Helping Poorer Ones the Most Ordinal Classification Using Hybrid Artificial Neural Networks with Projection and Kernel Basis Functions [View Less]
Projects
Modelos de Aprendizaje de Máquina para la determinación óptima de la Supervivencia y la Asignación Donante/REceptor en trasplante hepático. MASS-ALLOCATION Algoritmos de clasificación ordinal en energias renovables (ORdinal Classification and prediction Algorithms in Renewable Energy, ORCA-RE) NEMOTECH: Técnicas de Neuro-Modelado utilizando Algoritmos de Aprendizaje Híbridos. Aplicaciones en Biomedicina de Trasplantes, Agronomía y Microbiología Predictiva