A5050268688- Metaheuristic Optimization Algorithms Research
- Neural Networks and Applications
- Evolutionary Algorithms and Applications
- Advanced Multi-Objective Optimization Algorithms
- Wireless Networks and Protocols
- Hydrological Forecasting Using AI
- IPv6, Mobility, Handover, Networks, Security
- Machine Learning and Data Classification
- Energy Load and Power Forecasting
- Fault Detection and Control Systems
- Liver Disease Diagnosis and Treatment
- Advanced Wireless Network Optimization
- Thyroid Disorders and Treatments
- Spectroscopy and Chemometric Analyses
- Fuzzy Logic and Control Systems
- Face and Expression Recognition
- Finance, Taxation, and Governance
- Imbalanced Data Classification Techniques
- Thyroid Cancer Diagnosis and Treatment
- Social Sciences and Policies
- E-Learning and Knowledge Management
- Grey System Theory Applications
- Organ Transplantation Techniques and Outcomes
- Labor Law and Work Dynamics
- Knowledge Societies in the 21st Century
University of Córdoba
2015-2024
Instituto Maimónides de Investigación Biomédica de Córdoba
2024
Universidad de Sevilla
1998-2023
Instituto Hispalense de Pediatria
2023
Misión Biológica de Galicia
2021-2023
Universidad Complutense de Madrid
2023
Universidad de Granada
2016-2021
Hospital de Galdakao
2020
Central University Hospital of Asturias
2014-2019
University of Cartagena
2010-2018
This paper proposes a multiclassification algorithm using multilayer perceptron neural network models. It tries to boost two conflicting main objectives of multiclassifiers: high correct classification rate level and for each class. last objective is not usually optimized in classification, but considered here given the need obtain precision class real problems. To solve this machine learning problem, we use Pareto-based multiobjective optimization methodology based on memetic evolutionary...
In next generation wireless networks, Internet service providers (ISPs) are expected to offer services through several technologies (e.g., WLAN, 3G, WiFi, and WiMAX). Thus, mobile computers equipped with multiple interfaces will be able maintain simultaneous connections different networks increase their data communication rates by aggregating the bandwidth available at these networks. To guarantee quality-of-service (QoS) for applications, this paper proposes a dynamic QoS negotiation scheme...
Abstract Dopamine is a recognized modulator in the central nervous system (CNS) and peripheral organ functions. The presence of dopamine receptors outside CNS has suggested an intriguing interaction between other functional systems, such as reproductive system. In present study we analyzed expression D2R rat testis, spermatogenic cells spermatozoa, different mammals. RT‐PCR analysis testis mRNA showed specific bands corresponding to two receptor (L S) isoforms previously described brain....
This paper proposes a novel methodology for recovering missing time series data, crucial task subsequent Machine Learning (ML) analyses. The is specifically applied to Significant Wave Height (SWH) in the field of marine engineering. proposed approach involves two phases. Firstly, SWH each buoy independently reconstructed using three transfer function models: regression-based, correlation-based, and distance-based. distance-based exhibits best overall performance. Secondly, Evolutionary...
In this work, a problem of optimal placement renewable generation and topology design for Microgrid (MG) is tackled. The consists determining the MG nodes where energy generators must be optimally located also optimization design, i.e., deciding which should connected lines’ cross-sectional areas (CSA). For purpose, multi-objective with two conflicting objectives has been used, utilizing cost lines, C, higher as CSA increases, losses, E, lower increases. To characterize loads to nodes,...
Meteorological data are extensively used to perform environmental learning. Soft Computing (SC) and Machine Learning (ML) techniques represent a valuable support in many research areas, but require datasets containing information related the topic under study. Such not always available an appropriate format its preparation pre-processing implies lot of time effort by researchers. This paper presents novel software tool with user-friendly GUI create means management integration meteorological...
Dropout is a popular regularisation tool for deep neural classifiers, but it applied regardless of the nature classification task: nominal or ordinal. Consequently, order relation between class labels ordinal problems ignored. In this paper, we propose fusion standard dropout and new methodology regularising networks to avoid overfitting improve generalisation, taking into account extra information task, which exploited performance. The correlation outputs every neuron target used guide...
This paper proposes a neural network model for wind speed prediction, very important task in parks management. Currently, several physical-statistical and artificial intelligence (AI) prediction models are used to this end. A recently proposed hybrid is based on hybridizations of global mesoscale forecasting systems, with final downscaling step using multilayer perceptron (MLP). In paper, we test an alternative downscaling, which projection hyperbolic tangent units (HTUs) within feed forward...
Brassica rapa is grown in northwestern Spain to obtain turnip greens. The tops of the same plants (flower stems with buds) are cut and sell as tops, increasing value crop. This practice could be extended other brassicas. objectives this work study phytochemical potential coles (Brassica oleracea) leaf rape napus) compared compare different (cabbage, kale, tronchuda cabbage), which differ their morphology use. We evaluated content glucosinolates phenolic compounds antioxidant capacity leaves...