Alicia Troncoso Lora

发表

A local search in Scatter Search for improving Biclusters

Juan A. Nepomuceno, Alicia Troncoso Lora, Jesús S. Aguilar-Ruiz, 2011, 2011 Third World Congress on Nature and Biologically Inspired Computing.

Improving Time Series Forecasting by Discovering Frequent Episodes in Sequences

Alicia Troncoso Lora, José Cristóbal Riquelme Santos, Francisco Martínez-Álvarez, 2009, IDA.

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

Alicia Troncoso Lora, Francisco Martínez-Álvarez, José F. Torres, 2017, IWINAC.

Discovery of motifs to forecast outlier occurrence in time series

Alicia Troncoso Lora, Jesús S. Aguilar-Ruiz, José Cristóbal Riquelme Santos, 2011, Pattern Recognit. Lett..

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

Alicia Troncoso Lora, Francisco Martínez-Álvarez, Emilio Florido, 2015, SOCO.

Mining quantitative association rules based on evolutionary computation and its application to atmospheric pollution

Alicia Troncoso Lora, José Cristóbal Riquelme Santos, Francisco Martínez-Álvarez, 2010, Integr. Comput. Aided Eng..

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

Alicia Troncoso Lora, José Cristóbal Riquelme Santos, Francisco Martínez-Álvarez, 2015, Neurocomputing.

A Kernel for Time Series Classification: Application to Atmospheric Pollutants

Alicia Troncoso Lora, José Cristóbal Riquelme Santos, Marta Arias, 2012, SOCO.

Big data solar power forecasting based on deep learning and multiple data sources

Irena Koprinska, Alicia Troncoso Lora, Zheng Wang, 2019, Expert Syst. J. Knowl. Eng..

A scalable approach based on deep learning for big data time series forecasting

Alicia Troncoso Lora, Francisco Martínez-Álvarez, José F. Torres, 2018, Integr. Comput. Aided Eng..

Real-Time Big Data Analytics in Smart Cities from LoRa-Based IoT Networks

Alicia Troncoso Lora, Francisco Martínez-Álvarez, David Gutiérrez-Avilés, 2019, SOCO.

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

Juan A. Nepomuceno, Alicia Troncoso Lora, Jesús S. Aguilar-Ruiz, 2015, Appl. Soft Comput..

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

Alicia Troncoso Lora, José Cristóbal Riquelme Santos, Marta Arias, 2015, Neurocomputing.

Scalable Forecasting Techniques Applied to Big Electricity Time Series

Alicia Troncoso Lora, Francisco Martínez-Álvarez, José F. Torres, 2017, IWANN.

An Overlapping Control–Biclustering Algorithm from Gene Expression Data

Juan A. Nepomuceno, Alicia Troncoso Lora, Jesús S. Aguilar-Ruiz, 2009, 2009 Ninth International Conference on Intelligent Systems Design and Applications.

Applications of Computational Intelligence in Time Series

Alicia Troncoso Lora, José Cristóbal Riquelme Santos, Francisco Martínez-Álvarez, 2017, Comput. Intell. Neurosci..

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

Alicia Troncoso Lora, José Cristóbal Riquelme Santos, Francisco Martínez-Álvarez, 2013, SOCO-CISIS-ICEUTE.

Inferring gene coexpression networks with Biclustering based on Scatter Search

Juan A. Nepomuceno, Alicia Troncoso Lora, Jesús S. Aguilar-Ruiz, 2011, 2011 11th International Conference on Intelligent Systems Design and Applications.

Big data time series forecasting based on pattern sequence similarity and its application to the electricity demand

Alicia Troncoso Lora, Francisco Martínez-Álvarez, Gualberto Asencio-Cortés, 2020, Inf. Sci..

Application of Evolutionary Computation Techniques to the Optimal Short-Term Scheduling of the Electrical Energy Production

Alicia Troncoso Lora, Antonio Gómez Expósito, José Cristóbal Riquelme Santos, 2003, Conferencia de la Asociación Española para la Inteligencia Artificial.

Special issue on Hybrid Artificial Intelligence Systems from HAIS 2016 Conference

Héctor Quintián-Pardo, Emilio Corchado, Alicia Troncoso Lora, 2019, Neurocomputing.

Automated Spark Clusters Deployment for Big Data with Standalone Applications Integration

Alicia Troncoso Lora, Francisco Martínez-Álvarez, José F. Torres, 2016, CAEPIA.

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

Alicia Troncoso Lora, José Cristóbal Riquelme Santos, Jaume Bacardit, 2015, Integr. Comput. Aided Eng..

A Comparison of Two Techniques for Next-Day Electricity Price Forecasting

Alicia Troncoso Lora, Antonio Gómez Expósito, José Cristóbal Riquelme Santos, 2002, IDEAL.

Static and Dynamic Ensembles of Neural Networks for Solar Power Forecasting

Irena Koprinska, Alicia Troncoso Lora, Zheng Wang, 2018, 2018 International Joint Conference on Neural Networks (IJCNN).

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

Juan A. Nepomuceno, Alicia Troncoso Lora, Jesús S. Aguilar-Ruiz, 2018, BioData Mining.

Electricity Market Price Forecasting: Neural Networks versus Weighted-Distance k Nearest Neighbours

Alicia Troncoso Lora, Antonio Gómez Expósito, José Cristóbal Riquelme Santos, 2002, DEXA.

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

Alicia Troncoso Lora, Jesús S. Aguilar-Ruiz, José Cristóbal Riquelme Santos, 2008, Eur. J. Oper. Res..

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

Amparo Alonso-Betanzos, Alicia Troncoso Lora, Oscar Luaces, 2015, Knowl. Based Syst..

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

Alicia Troncoso Lora, Francisco Martínez-Álvarez, María Martínez-Ballesteros, 2016, HAIS.

Improving Earthquake Prediction with Principal Component Analysis: Application to Chile

Alicia Troncoso Lora, Francisco Martínez-Álvarez, Gualberto Asencio-Cortés, 2015, HAIS.

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

Amparo Alonso-Betanzos, Alicia Troncoso Lora, Oscar Luaces, 2015, 2015 IEEE International Conference on Data Mining Workshop (ICDMW).

Evolutionary metaheuristic for biclustering based on linear correlations among genes

Juan A. Nepomuceno, Alicia Troncoso Lora, Jesús S. Aguilar-Ruiz, 2010, SAC '10.

Obtaining optimal quality measures for quantitative association rules

Alicia Troncoso Lora, José Cristóbal Riquelme Santos, Francisco Martínez-Álvarez, 2016, Neurocomputing.

High-content screening images streaming analysis using the STriGen methodology

Alicia Troncoso Lora, Cristina Rubio-Escudero, David Gutiérrez-Avilés, 2020, SAC.

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

Alicia Troncoso Lora, Jesús S. Aguilar-Ruiz, José Cristóbal Riquelme Santos, 2008, 2008 Eighth IEEE International Conference on Data Mining.

Computational Intelligence Techniques for Predicting Earthquakes

Alicia Troncoso Lora, José Cristóbal Riquelme Santos, Francisco Martínez-Álvarez, 2011, HAIS.

Automated Deployment of a Spark Cluster with Machine Learning Algorithm Integration

Alicia Troncoso Lora, Francisco Martínez-Álvarez, David Gutiérrez-Avilés, 2020, Big Data Res..

An evolutionary algorithm to discover quantitative association rules in multidimensional time series

Alicia Troncoso Lora, José Cristóbal Riquelme Santos, Francisco Martínez-Álvarez, 2011, Soft Comput..

Quantitative Association Rules Applied to Climatological Time Series Forecasting

Alicia Troncoso Lora, José Cristóbal Riquelme Santos, Francisco Martínez-Álvarez, 2009, IDEAL.

Impact of Auto-evaluation Tests as Part of the Continuous Evaluation in Programming Courses

Alicia Troncoso Lora, José Cristóbal Riquelme Santos, Francisco Martínez-Álvarez, 2018, SOCO-CISIS-ICEUTE.

Partitioning-Clustering Techniques Applied to the Electricity Price Time Series

Alicia Troncoso Lora, José Cristóbal Riquelme Santos, Francisco Martínez-Álvarez, 2007, IDEAL.

Correlation-Based Scatter Search for Discovering Biclusters from Gene Expression Data

Juan A. Nepomuceno, Alicia Troncoso Lora, Jesús S. Aguilar-Ruiz, 2010, EvoBIO.

Solar Power Forecasting Based on Pattern Sequence Similarity and Meta-learning

Irena Koprinska, Mashud Rana, Alicia Troncoso Lora, 2020, ICANN.

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

Alicia Troncoso Lora, José Cristóbal Riquelme Santos, Francisco Martínez-Álvarez, 2016, Knowledge and Information Systems.

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

Alicia Troncoso Lora, Jesús S. Aguilar-Ruiz, José Cristóbal Riquelme Santos, 2007, Twentieth IEEE International Symposium on Computer-Based Medical Systems (CBMS'07).

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

Alicia Troncoso Lora, Francisco Martínez-Álvarez, Gualberto Asencio-Cortés, 2015, Neural Computing and Applications.

A novel spark-based multi-step forecasting algorithm for big data time series

Alicia Troncoso Lora, Francisco Martínez-Álvarez, José F. Torres, 2018, Inf. Sci..

Coronavirus Optimization Algorithm: A bioinspired metaheuristic based on the COVID-19 propagation model

Alicia Troncoso Lora, José Cristóbal Riquelme Santos, Francisco Martínez-Álvarez, 2020, Big Data.

Pattern Sequence Neural Network for Solar Power Forecasting

Irena Koprinska, Mashud Rana, Alicia Troncoso Lora, 2019, ICONIP.

Advances in optimization and prediction techniques: Real-world applications

Alicia Troncoso Lora, 2006, AI Commun..

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

Alicia Troncoso Lora, Francisco Martínez-Álvarez, Rubén Pérez-Chacón, 2018, Knowl. Based Syst..

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

Irena Koprinska, Mashud Rana, Alicia Troncoso Lora, 2013, The 2013 International Joint Conference on Neural Networks (IJCNN).

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

Alicia Troncoso Lora, Amparo Alonso-Betanzos, Oscar Luaces, 2017, Knowl. Based Syst..

Extended Weighted Nearest Neighbor for Electricity Load Forecasting

Irena Koprinska, Mashud Rana, Alicia Troncoso Lora, 2016, ICANN.

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

Juan A. Nepomuceno, Alicia Troncoso Lora, Jesús S. Aguilar-Ruiz, 2009, PRIB.

Biclustering of Gene Expression Data by Correlation-Based Scatter Search

Juan A. Nepomuceno, Alicia Troncoso Lora, Jesús S. Aguilar-Ruiz, 2011, BioData Mining.

Random Hyper-parameter Search-Based Deep Neural Network for Power Consumption Forecasting

Alicia Troncoso Lora, Francisco Martínez-Álvarez, David Gutiérrez-Avilés, 2019, IWANN.

Discovering Spatio-Temporal Patterns in Precision Agriculture Based on Triclustering

Alicia Troncoso Lora, Francisco Martínez-Álvarez, Maria Teresa Godinho, 2020, SOCO.

Biclustering of Gene Expression Data Based on SimUI Semantic Similarity Measure

Juan A. Nepomuceno, Alicia Troncoso Lora, Jesús S. Aguilar-Ruiz, 2016, HAIS.

Using principal component analysis to improve earthquake magnitude prediction in Japan

Alicia Troncoso Lora, Francisco Martínez-Álvarez, Gualberto Asencio-Cortés, 2017, Log. J. IGPL.

Forecasting hourly electricity load profile using neural networks

Irena Koprinska, Mashud Rana, Alicia Troncoso Lora, 2014, 2014 International Joint Conference on Neural Networks (IJCNN).

SmartFD: A Real Big Data Application for Electrical Fraud Detection

Alicia Troncoso Lora, José Cristóbal Riquelme Santos, Francisco Martínez-Álvarez, 2018, HAIS.

ra A Sensitivity Analysis for Quality Measures of Quantitative Association Rules

Alicia Troncoso Lora, José Cristóbal Riquelme Santos, Francisco Martínez-Álvarez, 2013, HAIS.

Time-Series Clustering Based on the Characterization of Segment Typologies

Pedro Antonio Gutiérrez, César Hervás-Martínez, Alicia Troncoso Lora, 2018, IEEE Transactions on Cybernetics.

A novel methodology to predict urban traffic congestion with ensemble learning

Alicia Troncoso Lora, Francisco Martínez-Álvarez, Gualberto Asencio-Cortés, 2016, Soft Comput..

Deep Learning for Big Data Time Series Forecasting Applied to Solar Power

Irena Koprinska, Alicia Troncoso Lora, Zheng Wang, 2018, SOCO-CISIS-ICEUTE.

Time-Series Prediction: Application to the Short-Term Electric Energy Demand

Alicia Troncoso Lora, Antonio Gómez Expósito, José Cristóbal Riquelme Santos, 2003, CAEPIA.

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

Juan A. Nepomuceno, Alicia Troncoso Lora, Jesús S. Aguilar-Ruiz, 2015, Comput. Methods Programs Biomed..

Biclusters Evaluation Based on Shifting and Scaling Patterns

Juan A. Nepomuceno, Alicia Troncoso Lora, Jesús S. Aguilar-Ruiz, 2007, IDEAL.

MV-kWNN: A novel multivariate and multi-output weighted nearest neighbours algorithm for big data time series forecasting

Alicia Troncoso Lora, Francisco Martínez-Álvarez, Rubén Pérez-Chacón, 2019, Neurocomputing.

Imbalanced classification techniques for monsoon forecasting based on a new climatic time series

Alicia Troncoso Lora, Gualberto Asencio-Cortés, P. Ribera, 2017, Environ. Model. Softw..

Pattern recognition to forecast seismic time series

Alicia Troncoso Lora, Francisco Martínez-Álvarez, Antonio Morales-Esteban, 2010, Expert Syst. Appl..

Influence of kNN-Based Load Forecasting Errors on Optimal Energy Production

Alicia Troncoso Lora, Antonio Gómez Expósito, José Cristóbal Riquelme Santos, 2003, EPIA.

Finding Electric Energy Consumption Patterns in Big Time Series Data

Alicia Troncoso Lora, Francisco Martínez-Álvarez, Rubén Pérez-Chacón, 2016, DCAI.

Selecting the best measures to discover quantitative association rules

Alicia Troncoso Lora, José Cristóbal Riquelme Santos, Francisco Martínez-Álvarez, 2014, Neurocomputing.

Implementation of an Internal Quality Assurance System at Pablo de Olavide University of Seville: Improving Computer Science Students Skills

Alicia Troncoso Lora, Francisco Martínez-Álvarez, Cristina Rubio-Escudero, 2019, CISIS-ICEUTE.

A New Forecasting Algorithm Based on Neighbors for Streaming Electricity Time Series

Alicia Troncoso Lora, Gualberto Asencio-Cortés, L. Melgar-García, 2020, HAIS.

Multi-step forecasting for big data time series based on ensemble learning

Irena Koprinska, Alicia Troncoso Lora, Francisco Martínez-Álvarez, 2019, Knowl. Based Syst..

Electricity Generation Forecasting in Concentrating Solar-Thermal Power Plants with Ensemble Learning

Alicia Troncoso Lora, Francisco Martínez-Álvarez, A. Melara, 2021, SOCO.

Electricity Consumption Time Series Forecasting Using Temporal Convolutional Networks

Alicia Troncoso Lora, Francisco Martínez-Álvarez, José F. Torres, 2021, CAEPIA.

Nearest Neighbors-Based Forecasting for Electricity Demand Time Series in Streaming

Alicia Troncoso Lora, Cristina Rubio-Escudero, David Gutiérrez-Avilés, 2021, CAEPIA.

Discovering three-dimensional patterns in real-time from data streams: An online triclustering approach

Alicia Troncoso Lora, Cristina Rubio-Escudero, David Gutiérrez-Avilés, 2021, Inf. Sci..

HLNet: A Novel Hierarchical Deep Neural Network for Time Series Forecasting

Alicia Troncoso Lora, Gualberto Asencio-Cortés, M. J. Jiménez-Navarro, 2021, SOCO.

Finding improved local minima of power system optimization problems by interior-point methods

Alicia Troncoso Lora, José Cristóbal Riquelme Santos, Antonio Gomez-Exposito, 2002 .

INFLUENCE OF ANN-BASED MARKET PRICE FORECASTING UNCERTAINTY ON OPTIMAL BIDDING

Alicia Troncoso Lora, A. T. Lora, G Antonio, 2002 .