Browsing by Author "Troncoso Lora, Alicia"
Now showing items 1-20 of 65
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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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Presentation
A Hybrid Metaheuristic for Biclustering Based on Scatter Search and Genetic Algorithms
(Springer, 2009)In this paper a hybrid metaheuristic for biclustering based on Scatter Search and Genetic Algorithms is presented. A ...
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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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Presentation
A Local Search in Scatter Search for Improving Biclusters
(IEEE Computer Society, 2011)Scatter Search is a population-based metaheuristic that emphasizes systematic processes against random proce dures. A ...
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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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Presentation
A Nearest Neighbours-Based Algorithm for Big Time Series Data Forecasting
(Springer, 2016)A forecasting algorithm for big data time series is presented in this work. A nearest neighbours-based strategy is adopted ...
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Article
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 ...
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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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Presentation
An Overlapping Control–Biclustering Algorithm from Gene Expression Data
(IEEE Computer Society, 2009)In this paper a hybrid metaheuristic for biclustering based on Scatter Search and Genetic Algorithms is pre sented. A ...
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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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Article
Applications of Computational Intelligence in Time Series
(Hindawi, 2017) -
Article
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 ...
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Presentation
Biclustering of Gene Expression Data Based on SimUI Semantic Similarity Measure
(Springer, 2016)Biclustering is an unsupervised machine learning technique that simultaneously clusters genes and conditions in gene ...
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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 ...