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Capítulo de Libro
A Comparative Study between Two Regression Methods on LiDAR Data: A Case Study
(Springer, 2011)
Airborne LiDAR (Light Detection and Ranging) has become an excellent tool for accurately assessing vegetation characteristics in forest environments. Previous studies showed empirical relationships between LiDAR and ...
Artículo
Enhancing the scalability of a genetic algorithm to discover quantitative association rules in large-scale datasets
(iOS Press, 2015)
Association rule mining is a well-known methodology to discover significant and apparently hidden relations among attributes in a subspace of instances from datasets. Genetic algorithms have been extensively used to find ...
Ponencia
A Preliminary Study of the Suitability of Deep Learning to Improve LiDAR-Derived Biomass Estimation
(Springer, 2016)
Light Detection and Ranging (LiDAR) is a remote sensor able to extract three-dimensional information about forest structure. Bio physical models have taken advantage of the use of LiDAR-derived infor mation to improve ...
Artículo
Semi-wrapper feature subset selector for feed-forward neural networks: Applications to binary and multi-class classification problems
(ScienceDirect, 2019-08-11)
This paper explores widely the data preparation stage within the process of knowledge discovery and data mining via feature subset selection in the context of two very well-known neural models: radial basis function neural ...
Capítulo de Libro
Inferring Gene-Gene Associations from Quantitative Association Rules
(IEEE, 2011)
The microarray technique is able to monitor the change in concentration of RNA in thousands of genes simultaneously. The interest in this technique has grown exponentially in recent years and the difficulties in analyzing ...
Ponencia
Deleting or Keeping Outliers for Classifier Training?
(IEEE, 2014)
This paper introduces two statistical outlier detection approaches by classes. Experiments on binary and multi-class classification problems reveal that the partial removal of outliers improves significantly one or ...
Artículo
Applications of Computational Intelligence in Time Series
(Hindawi, 2017)
Artículo
Energy Time Series Forecasting Based on Pattern Sequence Similarity
(IEEE, 2011)
This paper presents a new approach to forecast the behavior of time series based on similarity of pattern sequences. First, clustering techniques are used with the aim of grouping and labeling the samples from a data set. ...
Capítulo de Libro
Label Dependent Evolutionary Feature Weighting for Remote Sensing Data
(2010)
Nearest neighbour (NN) is a very common classifier used to develop important remote sensing products like land use and land cover (LULC) maps. Evolutive computation has often been used to obtain feature weighting in order ...
Ponencia
Diez años innovando en la enseñanza de los fundamentos de la programación: resultados y conclusiones
(Asociación de Enseñantes Universitarios de la Informática (AENUI), 2012)
Este artículo presenta los cambios experimentados en las asignaturas relacionadas con la introducción a la programación, impartidas en las titulaciones de Ingeniería Informática de la Universidad de Sevilla durante el ...