List of works - Alicia Troncoso

A Comparative Study of Machine Learning Regression Methods on LiDAR Data: A Case Study

scientific article published in 2014

A Hybrid Metaheuristic for Biclustering Based on Scatter Search and Genetic Algorithms

scientific article published in 2009

A Kernel for Time Series Classification: Application to Atmospheric Pollutants

scientific article published in 2013

A Nearest Neighbours-Based Algorithm for Big Time Series Data Forecasting

scientific article published in 2016

A New Methodology Based on Imbalanced Classification for Predicting Outliers in Electricity Demand Time Series

scientific article published on 14 September 2016

A Sensitivity Analysis for Quality Measures of Quantitative Association Rules

scientific article published in 2013

A Survey on Data Mining Techniques Applied to Electricity-Related Time Series Forecasting

scientific article published on 19 November 2015

A comparison of machine learning regression techniques for LiDAR-derived estimation of forest variables

scientific article published in November 2015

A factorization approach to evaluate open-response assignments in MOOCs using preference learning on peer assessments

scientific article published in September 2015

A local search in Scatter Search for improving Biclusters

scientific article published in October 2011

A multi-scale smoothing kernel for measuring time-series similarity

scientific article published in November 2015

A novel methodology to predict urban traffic congestion with ensemble learning

scientific article published on 3 August 2016

An Overlapping Control–Biclustering Algorithm from Gene Expression Data

scientific article published in 2009

Applications of Computational Intelligence in Time Series

scientific article published on 22 May 2017

Automated Spark Clusters Deployment for Big Data with Standalone Applications Integration

scientific article published in 2016

Biclustering of Gene Expression Data Based on SimUI Semantic Similarity Measure

scientific article published in 2016

Biclustering of Gene Expression Data by Correlation-Based Scatter Search ⬇️

scientific article published on January 24, 2011

Big Data Analytics for Discovering Electricity Consumption Patterns in Smart Cities

scientific article published on 18 March 2018

Big data time series forecasting based on nearest neighbours distributed computing with Spark

scientific article published in December 2018

Combining pattern sequence similarity with neural networks for forecasting electricity demand time series

scientific article published in August 2013

Computational Intelligence Techniques for Predicting Earthquakes

scientific article published in 2011

Content-based methods in peer assessment of open-response questions to grade students as authors and as graders

scientific article published in February 2017

Data Mining for Predicting Traffic Congestion and Its Application to Spanish Data

scientific article published in 2015

Data Science and Big Data in Energy Forecasting

scientific article published on 21 November 2018

Deep Learning-Based Approach for Time Series Forecasting with Application to Electricity Load

scientific article published in 2017

Detection of Microcalcifications in Mammographies Based on Linear Pixel Prediction and Support-Vector Machines

scientific article published in June 2007

Discovery of motifs to forecast outlier occurrence in time series

scientific article published in September 2011

Enhancing the scalability of a genetic algorithm to discover quantitative association rules in large-scale datasets

scientific article published in January 2015

Evolutionary techniques applied to the optimal short-term scheduling of the electrical energy production

scientific article published in March 2008

Extended Weighted Nearest Neighbor for Electricity Load Forecasting

scientific article published in 2016

Finding Electric Energy Consumption Patterns in Big Time Series Data

scientific article published in 2016

Forecasting hourly electricity load profile using neural networks

scientific article published in July 2014

Improving Earthquake Prediction with Principal Component Analysis: Application to Chile

scientific article published in 2015

Improving Time Series Forecasting by Discovering Frequent Episodes in Sequences

scientific article published in 2009

Improving a multi-objective evolutionary algorithm to discover quantitative association rules

scientific article published on 24 December 2015

Including Content-Based Methods in Peer-Assessment of Open-Response Questions

scientific article published in November 2015

Inferring gene coexpression networks with Biclustering based on Scatter Search

scientific article published in November 2011

Integrating biological knowledge based on functional annotations for biclustering of gene expression data

scientific article published on 18 March 2015

LBF: A Labeled-Based Forecasting Algorithm and Its Application to Electricity Price Time Series

scientific article published in December 2008

Large Earthquake Magnitude Prediction in Chile with Imbalanced Classifiers and Ensemble Learning

scientific article published on 16 June 2017

Local models-based regression trees for very short-term wind speed prediction

scientific article published in September 2015

Medium–large earthquake magnitude prediction in Tokyo with artificial neural networks

scientific article published on 21 November 2015

Obtaining optimal quality measures for quantitative association rules

scientific article published in February 2016

Pairwise gene GO-based measures for biclustering of high-dimensional expression data.

scientific article published on 27 March 2018

Quantitative Association Rules Applied to Climatological Time Series Forecasting

scientific article published in 2009

Recent Advances in Energy Time Series Forecasting

scientific article published on 14 June 2017

Scalable Forecasting Techniques Applied to Big Electricity Time Series

scientific article published in 2017

Scatter search-based identification of local patterns with positive and negative correlations in gene expression data

scientific article published in October 2015

Selecting the best measures to discover quantitative association rules

scientific article published in February 2014

List of works by Alicia Troncoso

A Comparative Study of Machine Learning Regression Methods on LiDAR Data: A Case Study

A Hybrid Metaheuristic for Biclustering Based on Scatter Search and Genetic Algorithms

A Kernel for Time Series Classification: Application to Atmospheric Pollutants

A Nearest Neighbours-Based Algorithm for Big Time Series Data Forecasting

A New Methodology Based on Imbalanced Classification for Predicting Outliers in Electricity Demand Time Series

A Sensitivity Analysis for Quality Measures of Quantitative Association Rules

A Survey on Data Mining Techniques Applied to Electricity-Related Time Series Forecasting

A comparison of machine learning regression techniques for LiDAR-derived estimation of forest variables

A factorization approach to evaluate open-response assignments in MOOCs using preference learning on peer assessments

A local search in Scatter Search for improving Biclusters

A multi-scale smoothing kernel for measuring time-series similarity

A novel methodology to predict urban traffic congestion with ensemble learning

An Overlapping Control–Biclustering Algorithm from Gene Expression Data

Applications of Computational Intelligence in Time Series

Automated Spark Clusters Deployment for Big Data with Standalone Applications Integration

Biclustering of Gene Expression Data Based on SimUI Semantic Similarity Measure

Biclustering of Gene Expression Data by Correlation-Based Scatter Search ⬇️

Big Data Analytics for Discovering Electricity Consumption Patterns in Smart Cities

Big data time series forecasting based on nearest neighbours distributed computing with Spark

Combining pattern sequence similarity with neural networks for forecasting electricity demand time series

Computational Intelligence Techniques for Predicting Earthquakes

Content-based methods in peer assessment of open-response questions to grade students as authors and as graders

Data Mining for Predicting Traffic Congestion and Its Application to Spanish Data

Data Science and Big Data in Energy Forecasting

Deep Learning-Based Approach for Time Series Forecasting with Application to Electricity Load

Detection of Microcalcifications in Mammographies Based on Linear Pixel Prediction and Support-Vector Machines

Discovery of motifs to forecast outlier occurrence in time series

Enhancing the scalability of a genetic algorithm to discover quantitative association rules in large-scale datasets

Evolutionary techniques applied to the optimal short-term scheduling of the electrical energy production

Extended Weighted Nearest Neighbor for Electricity Load Forecasting

Finding Electric Energy Consumption Patterns in Big Time Series Data

Forecasting hourly electricity load profile using neural networks

Improving Earthquake Prediction with Principal Component Analysis: Application to Chile

Improving Time Series Forecasting by Discovering Frequent Episodes in Sequences

Improving a multi-objective evolutionary algorithm to discover quantitative association rules

Including Content-Based Methods in Peer-Assessment of Open-Response Questions

Inferring gene coexpression networks with Biclustering based on Scatter Search

Integrating biological knowledge based on functional annotations for biclustering of gene expression data

LBF: A Labeled-Based Forecasting Algorithm and Its Application to Electricity Price Time Series

Large Earthquake Magnitude Prediction in Chile with Imbalanced Classifiers and Ensemble Learning

Local models-based regression trees for very short-term wind speed prediction

Medium–large earthquake magnitude prediction in Tokyo with artificial neural networks

Obtaining optimal quality measures for quantitative association rules

Pairwise gene GO-based measures for biclustering of high-dimensional expression data.

Quantitative Association Rules Applied to Climatological Time Series Forecasting

Recent Advances in Energy Time Series Forecasting

Scalable Forecasting Techniques Applied to Big Electricity Time Series

Scatter search-based identification of local patterns with positive and negative correlations in gene expression data

Selecting the best measures to discover quantitative association rules