Perfil del autor: Gutiérrez Avilés, David
Datos institucionales
| Nombre | Gutiérrez Avilés, David |
| Departamento | Lenguajes y Sistemas Informáticos |
| Área de conocimiento | Lenguajes y Sistemas Informáticos |
| Categoría profesional | Profesor Ayudante Doctor |
| Correo electrónico | Solicitar |
 |
|
Estadísticas
-
Nº publicaciones
25
-
Nº visitas
1698
-
Nº descargas
3998
| Publicaciones |
|---|
Capítulo de Libro
 Uso de herramientas software colaborativas para el seguimiento, estudio y evaluación de clases de enseñanzas prácticas y desarrollo
(Dykinson, 2024)
Para ayudar a la integración de todos los desarrollos individuales existen herramientas de control de versiones como ... |
Artículo
A new big data triclustering approach for extracting three-dimensional patterns in precision agriculture
(Elsevier, 2022)
Precision agriculture focuses on the development of site-specific harvest considering the variability of each crop ... |
Artículo
Deformation forecasting of a hydropower dam by hybridizing a long short-term memory deep learning network with the coronavirus optimization algorithm
(Wiley, 2022)
The safety operation and management of hydropower dam play a critical role in social-economic development and ensure ... |
Artículo
Data streams classification using deep learning under different speeds and drifts
(Oxford University Press, 2022)
Processing data streams arriving at high speed requires the development of models that can provide fast and accurate predictions. ... |
Ponencia
Nearest Neighbors-Based Forecasting for Electricity Demand Time Series in Streaming
(Springer, 2021)
This paper presents a new forecasting algorithm for time series in streaming named StreamWNN. The methodology has two ... |
Artículo
Discovering three-dimensional patterns in real-time from data streams: An online triclustering approach
(Elsevier, 2021)
Triclustering algorithms group sets of coordinates of 3-dimensional datasets. In this paper, a new triclustering approach ... |
Artículo
Generating a seismogenic source zone model for the Pyrenees: A GIS-assisted triclustering approach
(Elsevier, 2021)
Seismogenic source zone models, including the delineation and the characterization, still have a role to play in seismic ... |
Ponencia
Discovering Spatio-Temporal Patterns in Precision Agriculture Based on Triclustering
(Springer, 2020)
Agriculture has undergone some very important changes over the last few decades. The emergence and evolution of precision ... |
Artículo
Coronavirus Optimization Algorithm: A Bioinspired Metaheuristic Based on the COVID-19 Propagation Model
(Mary Ann Liebert, 2020)
This study proposes a novel bioinspired metaheuristic simulating how the coronavirus spreads and infects healthy people. ... |
Ponencia
High-Content Screening images streaming analysis using the STriGen methodology
(Association for Computing Machinery (ACM), 2020)
One of the techniques that provides systematic insights into biolog ical processes is High-Content Screening (HCS). It ... |
Artículo
Automated Deployment of a Spark Cluster with Machine Learning Algorithm Integration
(Elsevier, 2020)
The vast amount of data stored nowadays has turned big data analytics into a very trendy research field. The Spark distributed ... |
Ponencia
Random Hyper-parameter Search-Based Deep Neural Network for Power Consumption Forecasting
(Springer, 2019)
In this paper, we introduce a deep learning approach, based on feed-forward neural networks, for big data time series ... |
Ponencia
Real-Time Big Data Analytics in Smart Cities from LoRa-Based IoT Networks
(Springer, 2019)
The currently burst of the Internet of Things (IoT) tech-nologies implies the emergence of new lines of investigation ... |
Artículo
TRIQ: a new method to evaluate triclusters
(BMC: part of Springer Verlag, 2018)
Background: Triclustering has shown to be a valuable tool for the analysis of microarray data since its appearance as an ... |
Ponencia
SmartFD: A Real Big Data Application for Electrical Fraud Detection
(Springer, 2018)
The main objective of this paper is the application of big data analytics to a real case in the field of smart electric ... |
Ponencia
TRIQ: A Comprehensive Evaluation Measure for Triclustering Algorithms
(Springer, 2016)
Triclustering has shown to be a valuable tool for the analysis of microarray data since its appearance as an improvement ... |
Tesis Doctoral
TrLab: Una metodología para la extracción y evaluación de patrones de comportamiento de grandes volúmenes de datos biológicos dependientes del tiempo
(2015)
La tecnología de microarray ha revolucionado la investigación biotecnológica gracias a la posibilidad de monitorizar los ... |
Artículo
MSL: A Measure to Evaluate Three-dimensional Patterns in Gene Expression Data
(SAGE Publications, 2015)
Microarray technology is highly used in biological research environments due to its ability to monitor the RNA concentration ... |
Artículo
A Novel Method for Seismogenic Zoning Based on Triclustering: Application to the Iberian Peninsula
(MDPI, 2015)
A previous definition of seismogenic zones is required to do a probabilistic seismic hazard analysis for areas of spread ... |
Ponencia
LSL: A new measure to evaluate triclusters
(IEEE Computer Society, 2014)
Microarray technology has led to a great advance in biological studies due to its ability to monitorize the RNA levels of ... |
Artículo
TriGen: A genetic algorithm to mine triclusters in temporal gene expression data
(Elsevier, 2014)
Analyzing microarray data represents a computational challenge due to the characteristics of these data. Clustering techniques ... |
Artículo
Mining 3D Patterns from Gene Expression Temporal Data: A New Tricluster Evaluation Measure
(Hindawi, 2014)
Microarrays have revolutionized biotechnological research.The analysis of newdata generated represents a computational ... |
Ponencia
Triclustering on TemporaryMicroarray Data using the TriGen Algorithm
(IEEE, 2011)
The analysis of microarray data is a computational challenge due to the characteristics of these data. Clustering techniques ... |
Capítulo de Libro
Revisiting the Yeast Cell Cycle Problem with the Improved TriGen Algorithm
(IEEE, 2011)
Analyzing microarray data represents a computational challenge due to the characteristics of these data. Clustering ... |
Capítulo de Libro
Unravelling the Yeast Cell Cycle Using the TriGen Algorithm
(Springer, 2011)
Analyzing microarray data represents a computational challenge due to the characteristics of these data. Clustering ... |