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Mostrando ítems 1-10 de 14
Capítulo de Libro
Partitioning-Clustering Techniques Applied to the Electricity Price Time Series
(2007)
Clustering is used to generate groupings of data from a large dataset, with the intention of representing the behavior of a system as accurately as possible. In this sense, clustering is applied in this work to extract ...
Capítulo de Libro
Quantitative Association Rules Applied to Climatological Time Series Forecasting
(2009)
This work presents the discovering of association rules based on evolutionary techniques in order to obtain relationships among correlated time series. For this purpose, a genetic algorithm has been proposed to determine ...
Capítulo de Libro
Time-Series Prediction: Application to the Short-Term Electric Energy Demand
(2003)
This paper describes a time-series prediction method based on the kNN technique. The proposed methodology is applied to the 24-hour load forecasting problem. Also, based on recorded data, an alternative model is developed ...
Capítulo de Libro
A Comparative Study of Machine Learning Regression Methods on LiDAR Data: A Case Study
(Springer, 2014)
Light Detection and Ranging (LiDAR) is a remote sensor able to extract vertical information from sensed objects. LiDAR-derived information is nowadays used to develop environmental models for describing fire behaviour ...
Capítulo de Libro
LBF: A Labeled-Based Forecasting Algorithm and Its Application to Electricity Price Time Series
(2008)
A new approach is presented in this work with the aim of predicting time series behaviors. A previous labeling of the samples is obtained utilizing clustering techniques and the forecasting is applied using the information ...
Capítulo de Libro
Application of Evolutionary Computation Techniques to the Optimal Short-Term Scheduling of the Electrical Energy Production
(2003)
In this paper, an evolutionary technique applied to the optimal short-term scheduling (24 hours) of the electric energy production is presented. The equations that define the problem lead to a nonlinear mixed-integer ...
Capítulo de Libro
Improving Time Series Forecasting by Discovering Frequent Episodes in Sequences
(2009)
This work aims to improve an existing time series forecasting algorithm –LBF– by the application of frequent episodes techniques as a complementary step to the model. When real-world time series are forecasted, there exist ...
Capítulo de Libro
Detection of Microcalcifications in Mammographies Based on Linear Pixel Prediction and Support-Vector Machines
(2007)
Breast cancer is one of the diseases causing the largest number of deaths among women. Its early detection has been proved to be the most effective way to combat it. This work is focused on developing an integral tool able ...
Capítulo de Libro
A Kernel for Time Series Classification: Application to Atmospheric Pollutants
(Springer, 2013)
In this paper a kernel for time-series data is presented. The main idea of the kernel is that it is designed to recognize as similar time series that may be slightly shifted with one another. Namely, it tries to focus ...
Capítulo de Libro
A Sensitivity Analysis for Quality Measures of Quantitative Association Rules
(Springer, 2013)
There exist several fitness function proposals based on a combination of weighted objectives to optimize the discovery of association rules. Nevertheless, some differences in the measures used to assess the quality of ...