Browsing by Author "Troncoso Lora, Alicia"
Now showing items 1-20 of 36
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Chapter of Book
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. ...
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Article
A comparison of machine learning regression techniques for LiDAR-derived estimation of forest variables
(Elsevier, 2015)Light Detection and Ranging (LiDAR) is a remote sensor able to extract three-dimensional information. Environmental models ...
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Chapter of Book
A Comparison of Two Techniques for Next- Day Electricity Price Forecasting
(2002)In the framework of competitive markets, the market’s participants need energy price forecasts in order to determine their ...
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Chapter of Book
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 ...
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Article
A multi-scale smoothing kernel for measuring time-series similarity
(Elsevier, 2015)In this paper a kernel for time-series data is introduced so that it can be used for any data mining task that relies on ...
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Article
A novel ensemble method for electric vehicle power consumption forecasting: Application to the Spanish system
(Institute of Electrical and Electronics Engineers (IEEE), 2019)The use of electric vehicle across the world has become one of the most challenging issues for environmental policies. The ...
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Chapter of Book
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 ...
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Article
A Survey on Data Mining Techniques Applied to Energy Time Series Forecasting
(MDPI, 2015)Data mining has become an essential tool during the last decade to analyze large sets of data. The variety of techniques ...
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Article
An evolutionary algorithm to discover quantitative association rules in multidimensional time series
(Springer, 2011)An evolutionary approach for finding existing relationships among several variables of a multidimensional time series ...
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Chapter of Book
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 ...
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PhD Thesis
Biclustering sobre datos de expresión génica basado en búsqueda dispersa
(2015-07-21)Los datos de expresión génica, y su particular naturaleza e importancia, motivan no sólo el desarrollo de nuevas técnicas ...
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Article
Big Data Analytics for Discovering Electricity Consumption Patterns in Smart Cities
(MDPI, 2018)New technologies such as sensor networks have been incorporated into the management of buildings for organizations and ...
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Chapter of Book
Computational Intelligence Techniques for Predicting Earthquakes
(Springer, 2011)Nowadays, much effort is being devoted to develop techniques that forecast natural disasters in order to take ...
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Article
Data Science and Big Data in Energy Forecasting
(MDPI, 2018-11)This editorial summarizes the performance of the special issue entitled Data Science and Big Data in Energy Forecasting, ...
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Chapter of Book
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 ...
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Article
Discovery of motifs to forecast outlier occurrence in time series
(Elsevier, 2011)The forecasting process of real-world time series has to deal with especially unexpected values, commonly known as outliers. ...
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Article
Electricity Market Price Forecasting Based on Weighted Nearest Neighbors Techniques
(Institute of Electrical and Electronics Engineers (IEEE), 2007)This paper presents a simple technique to forecast next-day electricity market prices based on the weighted nearest neighbors ...
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Chapter of Book
Electricity Market Price Forecasting: Neural Networks versus Weighted-Distance k Nearest Neighbours
(2002)In today’s deregulated markets, forecasting energy prices is becoming more and more important. In the short term, expected ...
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Article
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. ...