Page
%P
-
Book Series
-
Book and Conference Proceedings
Theory and Applications of Time Series Analysis and Forecasting
Selected Contributions from ITISE 2021
-
Book and Conference Proceedings
-
Chapter and Conference Paper
Long- and Short-Term Approaches for Power Consumption Prediction Using Neural Networks
work reviews the challenge of power consumption prediction, approaching both short-term and long-term prediction problems using neural networks. A number of improvements are introduced for both prob...
-
Book and Conference Proceedings
-
Chapter and Conference Paper
Evaluating Multiple Sequence Alignments Using a LS-SVM Approach with a Heterogeneous Set of Biological Features
Multiple sequence alignment (MSA) is an essential approach to apply in other outstanding bioinformatics tasks such as structural predictions, biological function analyses or phylogenetic modeling. However, cur...
-
Chapter and Conference Paper
Handling Displacement Effects in On-Body Sensor-Based Activity Recognition
So far little attention has been paid to activity recognition systems limitations during out-of-lab daily usage. Sensor displacement is one of these major issues, particularly deleterious for inertial on-body ...
-
Chapter and Conference Paper
Activity Recognition Based on a Multi-sensor Meta-classifier
Ensuring ubiquity, robustness and continuity of monitoring is of key importance in activity recognition. To that end, multiple sensor configurations and fusion techniques are ever more used. In this paper we p...
-
Chapter
Evolutive Approaches for Variable Selection Using a Non-parametric Noise Estimator
The design of a model to approximate a function relies significantly on the data used in the training stage. The problem of selecting an adequate set of variables should be treated carefully due to its importa...
-
Article
Online self-evolving fuzzy controller with global learning capabilities
This paper presents an online self-evolving fuzzy controller with global learning capabilities. Starting from very simple or even empty configurations, the controller learns from its own actions while controll...
-
Chapter and Conference Paper
Novel Method for Feature-Set Ranking Applied to Physical Activity Recognition
Considerable attention is recently being paid in e-health and e-monitoring to the recognition of motion, postures and physical exercises from signal activity analysis. Most works are based on knowledge extract...
-
Chapter and Conference Paper
An Algorithm for Online Self-organization of Fuzzy Controllers
This work presents a fuzzy controller capable of designing its own structure online, based on the data obtained during the normal system operation. The algorithm does not use previous information about the dif...
-
Chapter and Conference Paper
Analysis of the Inducing Factors Involved in Stem Cell Differentiation Using Feature Selection Techniques, Support Vector Machines and Decision Trees
Stem cells represent a potential source of cells for regeneration, thanks to their ability to renew and differentiate into functional cells of different tissues. The studies and results related to stem cell di...
-
Chapter and Conference Paper
Creation of Specific-to-Problem Kernel Functions for Function Approximation
Although there is a large diversity in the literature related to kernel methods, there are only a few works which do not use kernels based on Radial Basis Functions (RBF) for regression problems. The reason fo...
-
Chapter and Conference Paper
Efficient Optimization of the Parameters of LS-SVM for Regression versus Cross-Validation Error
Least Squares Support Vector Machines (LS-SVM) are the state of the art in kernel methods for regression and function approximation. In the last few years, these models have been successfully applied to time s...
-
Article
Output value-based initialization for radial basis function neural networks
The use of Radial Basis Function Neural Networks (RBFNNs) to solve functional approximation problems has been addressed many times in the literature. When designing an RBFNN to approximate a function, the firs...
-
Chapter and Conference Paper
Parallel Multi-objective Memetic RBFNNs Design and Feature Selection for Function Approximation Problems
The design of Radial Basis Function Neural Networks (RBFNNs) still remains as a difficult task when they are applied to classification or to regression problems. The difficulty arises when the parameters that ...
-
Chapter and Conference Paper
Surface Modelling with Radial Basis Functions Neural Networks Using Virtual Environments
Modelling capabilities of Radial Basis Function Neural Networks (RBFNNs) are very dependent on four main factors: the number of neurons, the central location of each neuron, their associated weights and their ...
-
Chapter and Conference Paper
Kernel Methods Applied to Time Series Forecasting
Kernel methods are a class of algorithms whose importance has grown from the 90s in the machine learning field. Their most notable example are Support Vector Machines (SVMs), which are the state of the art for...
-
Chapter and Conference Paper
Use of ANNs as Classifiers for Selective Attention Brain-Computer Interfaces
Selective attention to visual-spatial stimuli causes decrements of power in alpha band and increments in beta. For steady-state visual evoked potentials (SSVEP) selective attention affects electroencephalogram...
