Alicia Troncoso Lora

Orcid: 0000-0002-9801-7999

Affiliations:
  • Pablo de Olavide University, Sevilla, Spain


According to our database1, Alicia Troncoso Lora authored at least 118 papers between 2002 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Bibliography

2024
Pattern sequence-based algorithm for multivariate big data time series forecasting: Application to electricity consumption.
Future Gener. Comput. Syst., 2024

Medium-term water consumption forecasting based on deep neural networks.
Expert Syst. Appl., 2024

Ground-Level Ozone Forecasting Using Explainable Machine Learning.
Proceedings of the Advances in Artificial Intelligence, 2024

An Experimental Comparison of Qiskit and Pennylane for Hybrid Quantum-Classical Support Vector Machines.
Proceedings of the Advances in Artificial Intelligence, 2024

2023
A novel semantic segmentation approach based on U-Net, WU-Net, and U-Net++ deep learning for predicting areas sensitive to pluvial flood at tropical area.
Int. J. Digit. Earth, December, 2023

Explainable hybrid deep learning and Coronavirus Optimization Algorithm for improving evapotranspiration forecasting.
Comput. Electron. Agric., December, 2023

A new Apache Spark-based framework for big data streaming forecasting in IoT networks.
J. Supercomput., July, 2023

FS-Studio: An extensive and efficient feature selection experimentation tool for Weka Explorer.
SoftwareX, July, 2023

A novel distributed forecasting method based on information fusion and incremental learning for streaming time series.
Inf. Fusion, July, 2023

A new approach based on association rules to add explainability to time series forecasting models.
Inf. Fusion, June, 2023

Streaming big time series forecasting based on nearest similar patterns with application to energy consumption.
Log. J. IGPL, March, 2023

Identifying novelties and anomalies for incremental learning in streaming time series forecasting.
Eng. Appl. Artif. Intell., 2023

Olive Oil Fly Population Pest Forecasting Using Explainable Deep Learning.
Proceedings of the 18th International Conference on Soft Computing Models in Industrial and Environmental Applications (SOCO 2023), 2023

Machine Learning Approaches for Predicting Tree Growth Trends Based on Basal Area Increment.
Proceedings of the 18th International Conference on Soft Computing Models in Industrial and Environmental Applications (SOCO 2023), 2023

Evolutionary computation to explain deep learning models for time series forecasting.
Proceedings of the 38th ACM/SIGAPP Symposium on Applied Computing, 2023

Deep Learning-Based Approach for Sleep Apnea Detection Using Physiological Signals.
Proceedings of the Advances in Computational Intelligence, 2023

A New Hybrid CNN-LSTM for Wind Power Forecasting in Ethiopia.
Proceedings of the Hybrid Artificial Intelligent Systems - 18th International Conference, 2023

Identification of Anomalies in Urban Sound Data with Autoencoders.
Proceedings of the Hybrid Artificial Intelligent Systems - 18th International Conference, 2023

Explainable Artificial Intelligence for Education: A Real Case of a University Subject Switched to Python.
Proceedings of the International Joint Conference 16th International Conference on Computational Intelligence in Security for Information Systems (CISIS 2023) 14th International Conference on EUropean Transnational Education (ICEUTE 2023), 2023

2022
A deep LSTM network for the Spanish electricity consumption forecasting.
Neural Comput. Appl., 2022

A new hybrid method for predicting univariate and multivariate time series based on pattern forecasting.
Inf. Sci., 2022

A new big data triclustering approach for extracting three-dimensional patterns in precision agriculture.
Neurocomputing, 2022

Special issue SOCO 2019: New trends in soft computing and its application in industrial and environmental problems.
Neurocomputing, 2022

Wrapper-based feature selection using regression trees to predict intrinsic viscosity of polymer.
Eng. Comput., 2022

A Cluster-Based Deep Learning Model for Energy Consumption Forecasting in Ethiopia.
Proceedings of the 17th International Conference on Soft Computing Models in Industrial and Environmental Applications (SOCO 2022), 2022

Explainable Artificial Intelligence for the Electric Vehicle Load Demand Forecasting Problem.
Proceedings of the 17th International Conference on Soft Computing Models in Industrial and Environmental Applications (SOCO 2022), 2022

A novel approach to discover numerical association based on the coronavirus optimization algorithm.
Proceedings of the SAC '22: The 37th ACM/SIGAPP Symposium on Applied Computing, Virtual Event, April 25, 2022

Explainable machine learning for sleep apnea prediction.
Proceedings of the Knowledge-Based and Intelligent Information & Engineering Systems: Proceedings of the 26th International Conference KES-2022, 2022

Nearest neighbors with incremental learning for real-time forecasting of electricity demand.
Proceedings of the IEEE International Conference on Data Mining Workshops, 2022

Olive Phenology Forecasting Using Information Fusion-Based Imbalanced Preprocessing and Automated Deep Learning.
Proceedings of the Hybrid Artificial Intelligent Systems - 17th International Conference, 2022

2021
Time-Series Clustering Based on the Characterization of Segment Typologies.
IEEE Trans. Cybern., 2021

Discovering three-dimensional patterns in real-time from data streams: An online triclustering approach.
Inf. Sci., 2021

Deep Learning for Time Series Forecasting: A Survey.
Big Data, 2021

Electricity Generation Forecasting in Concentrating Solar-Thermal Power Plants with Ensemble Learning.
Proceedings of the 16th International Conference on Soft Computing Models in Industrial and Environmental Applications, 2021

HLNet: A Novel Hierarchical Deep Neural Network for Time Series Forecasting.
Proceedings of the 16th International Conference on Soft Computing Models in Industrial and Environmental Applications, 2021

Electricity Consumption Time Series Forecasting Using Temporal Convolutional Networks.
Proceedings of the Advances in Artificial Intelligence, 2021

Nearest Neighbors-Based Forecasting for Electricity Demand Time Series in Streaming.
Proceedings of the Advances in Artificial Intelligence, 2021

2020
Big data time series forecasting based on pattern sequence similarity and its application to the electricity demand.
Inf. Sci., 2020

Coronavirus Optimization Algorithm: A Bioinspired Metaheuristic Based on the COVID-19 Propagation Model.
Big Data, 2020

Automated Deployment of a Spark Cluster with Machine Learning Algorithm Integration.
Big Data Res., 2020

Discovering Spatio-Temporal Patterns in Precision Agriculture Based on Triclustering.
Proceedings of the 15th International Conference on Soft Computing Models in Industrial and Environmental Applications, 2020

High-content screening images streaming analysis using the STriGen methodology.
Proceedings of the SAC '20: The 35th ACM/SIGAPP Symposium on Applied Computing, online event, [Brno, Czech Republic], March 30, 2020

Solar Power Forecasting Based on Pattern Sequence Similarity and Meta-learning.
Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2020, 2020

A New Forecasting Algorithm Based on Neighbors for Streaming Electricity Time Series.
Proceedings of the Hybrid Artificial Intelligent Systems - 15th International Conference, 2020

2019
Multi-step forecasting for big data time series based on ensemble learning.
Knowl. Based Syst., 2019

MV-kWNN: A novel multivariate and multi-output weighted nearest neighbours algorithm for big data time series forecasting.
Neurocomputing, 2019

Special issue on Hybrid Artificial Intelligence Systems from HAIS 2016 Conference.
Neurocomputing, 2019

Big data solar power forecasting based on deep learning and multiple data sources.
Expert Syst. J. Knowl. Eng., 2019

A Novel Ensemble Method for Electric Vehicle Power Consumption Forecasting: Application to the Spanish System.
IEEE Access, 2019

Real-Time Big Data Analytics in Smart Cities from LoRa-Based IoT Networks.
Proceedings of the 14th International Conference on Soft Computing Models in Industrial and Environmental Applications (SOCO 2019), 2019

Random Hyper-parameter Search-Based Deep Neural Network for Power Consumption Forecasting.
Proceedings of the Advances in Computational Intelligence, 2019

Pattern Sequence Neural Network for Solar Power Forecasting.
Proceedings of the Neural Information Processing - 26th International Conference, 2019

Implementation of an Internal Quality Assurance System at Pablo de Olavide University of Seville: Improving Computer Science Students Skills.
Proceedings of the International Joint Conference: 12th International Conference on Computational Intelligence in Security for Information Systems (CISIS 2019) and 10th International Conference on EUropean Transnational Education (ICEUTE 2019), 2019

2018
Big data time series forecasting based on nearest neighbours distributed computing with Spark.
Knowl. Based Syst., 2018

A novel spark-based multi-step forecasting algorithm for big data time series.
Inf. Sci., 2018

A scalable approach based on deep learning for big data time series forecasting.
Integr. Comput. Aided Eng., 2018

Imbalanced classification techniques for monsoon forecasting based on a new climatic time series.
Environ. Model. Softw., 2018

Time series clustering based on the characterisation of segment typologies.
CoRR, 2018

Pairwise gene GO-based measures for biclustering of high-dimensional expression data.
BioData Min., 2018

Deep Learning for Big Data Time Series Forecasting Applied to Solar Power.
Proceedings of the International Joint Conference SOCO'18-CISIS'18-ICEUTE'18, 2018

Impact of Auto-evaluation Tests as Part of the Continuous Evaluation in Programming Courses.
Proceedings of the International Joint Conference SOCO'18-CISIS'18-ICEUTE'18, 2018

Static and Dynamic Ensembles of Neural Networks for Solar Power Forecasting.
Proceedings of the 2018 International Joint Conference on Neural Networks, 2018

SmartFD: A Real Big Data Application for Electrical Fraud Detection.
Proceedings of the Hybrid Artificial Intelligent Systems - 13th International Conference, 2018

2017
Medium-large earthquake magnitude prediction in Tokyo with artificial neural networks.
Neural Comput. Appl., 2017

Content-based methods in peer assessment of open-response questions to grade students as authors and as graders.
Knowl. Based Syst., 2017

Using principal component analysis to improve earthquake magnitude prediction in Japan.
Log. J. IGPL, 2017

Applications of Computational Intelligence in Time Series.
Comput. Intell. Neurosci., 2017

Deep Learning-Based Approach for Time Series Forecasting with Application to Electricity Load.
Proceedings of the Biomedical Applications Based on Natural and Artificial Computing, 2017

Scalable Forecasting Techniques Applied to Big Electricity Time Series.
Proceedings of the Advances in Computational Intelligence, 2017

2016
A novel methodology to predict urban traffic congestion with ensemble learning.
Soft Comput., 2016

Improving a multi-objective evolutionary algorithm to discover quantitative association rules.
Knowl. Inf. Syst., 2016

Obtaining optimal quality measures for quantitative association rules.
Neurocomputing, 2016

Extended Weighted Nearest Neighbor for Electricity Load Forecasting.
Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2016, 2016

A Nearest Neighbours-Based Algorithm for Big Time Series Data Forecasting.
Proceedings of the Hybrid Artificial Intelligent Systems - 11th International Conference, 2016

Biclustering of Gene Expression Data Based on SimUI Semantic Similarity Measure.
Proceedings of the Hybrid Artificial Intelligent Systems - 11th International Conference, 2016

Finding Electric Energy Consumption Patterns in Big Time Series Data.
Proceedings of the Distributed Computing and Artificial Intelligence, 2016

Automated Spark Clusters Deployment for Big Data with Standalone Applications Integration.
Proceedings of the Advances in Artificial Intelligence, 2016

2015
A factorization approach to evaluate open-response assignments in MOOCs using preference learning on peer assessments.
Knowl. Based Syst., 2015

A multi-scale smoothing kernel for measuring time-series similarity.
Neurocomputing, 2015

A comparison of machine learning regression techniques for LiDAR-derived estimation of forest variables.
Neurocomputing, 2015

Enhancing the scalability of a genetic algorithm to discover quantitative association rules in large-scale datasets.
Integr. Comput. Aided Eng., 2015

Integrating biological knowledge based on functional annotations for biclustering of gene expression data.
Comput. Methods Programs Biomed., 2015

Scatter search-based identification of local patterns with positive and negative correlations in gene expression data.
Appl. Soft Comput., 2015

Data Mining for Predicting Traffic Congestion and Its Application to Spanish Data.
Proceedings of the 10th International Conference on Soft Computing Models in Industrial and Environmental Applications, 2015

Including Content-Based Methods in Peer-Assessment of Open-Response Questions.
Proceedings of the IEEE International Conference on Data Mining Workshop, 2015

Improving Earthquake Prediction with Principal Component Analysis: Application to Chile.
Proceedings of the Hybrid Artificial Intelligent Systems - 10th International Conference, 2015

2014
Selecting the best measures to discover quantitative association rules.
Neurocomputing, 2014

Forecasting hourly electricity load profile using neural networks.
Proceedings of the 2014 International Joint Conference on Neural Networks, 2014

2013
A Comparative Study of Machine Learning Regression Methods on LiDAR Data: A Case Study.
Proceedings of the International Joint Conference SOCO'13-CISIS'13-ICEUTE'13, 2013

Combining pattern sequence similarity with neural networks for forecasting electricity demand time series.
Proceedings of the 2013 International Joint Conference on Neural Networks, 2013

ra A Sensitivity Analysis for Quality Measures of Quantitative Association Rules.
Proceedings of the Hybrid Artificial Intelligent Systems - 8th International Conference, 2013

2012
A Kernel for Time Series Classification: Application to Atmospheric Pollutants.
Proceedings of the Soft Computing Models in Industrial and Environmental Applications, 2012

2011
Energy Time Series Forecasting Based on Pattern Sequence Similarity.
IEEE Trans. Knowl. Data Eng., 2011

An evolutionary algorithm to discover quantitative association rules in multidimensional time series.
Soft Comput., 2011

Discovery of motifs to forecast outlier occurrence in time series.
Pattern Recognit. Lett., 2011

Biclustering of Gene Expression Data by Correlation-Based Scatter Search.
BioData Min., 2011

A local search in Scatter Search for improving Biclusters.
Proceedings of the Third World Congress on Nature & Biologically Inspired Computing, 2011

Inferring gene coexpression networks with Biclustering based on Scatter Search.
Proceedings of the 11th International Conference on Intelligent Systems Design and Applications, 2011

Computational Intelligence Techniques for Predicting Earthquakes.
Proceedings of the Hybrid Artificial Intelligent Systems - 6th International Conference, 2011

2010
Mining quantitative association rules based on evolutionary computation and its application to atmospheric pollution.
Integr. Comput. Aided Eng., 2010

Pattern recognition to forecast seismic time series.
Expert Syst. Appl., 2010

Evolutionary metaheuristic for biclustering based on linear correlations among genes.
Proceedings of the 2010 ACM Symposium on Applied Computing (SAC), 2010

Correlation-Based Scatter Search for Discovering Biclusters from Gene Expression Data.
Proceedings of the Evolutionary Computation, 2010

2009
A Hybrid Metaheuristic for Biclustering Based on Scatter Search and Genetic Algorithms.
Proceedings of the Pattern Recognition in Bioinformatics, 2009

An Overlapping Control-Biclustering Algorithm from Gene Expression Data
Proceedings of the Ninth International Conference on Intelligent Systems Design and Applications, 2009

Quantitative Association Rules Applied to Climatological Time Series Forecasting.
Proceedings of the Intelligent Data Engineering and Automated Learning, 2009

Improving Time Series Forecasting by Discovering Frequent Episodes in Sequences.
Proceedings of the Advances in Intelligent Data Analysis VIII, 2009

2008
Evolutionary techniques applied to the optimal short-term scheduling of the electrical energy production.
Eur. J. Oper. Res., 2008

LBF: A Labeled-Based Forecasting Algorithm and Its Application to Electricity Price Time Series.
Proceedings of the 8th IEEE International Conference on Data Mining (ICDM 2008), 2008

2007
Biclusters Evaluation Based on Shifting and Scaling Patterns.
Proceedings of the Intelligent Data Engineering and Automated Learning, 2007

Partitioning-Clustering Techniques Applied to the Electricity Price Time Series.
Proceedings of the Intelligent Data Engineering and Automated Learning, 2007

Detection of Microcalcifications in Mammographies Based on Linear Pixel Prediction and Support-Vector Machines.
Proceedings of the 20th IEEE International Symposium on Computer-Based Medical Systems (CBMS 2007), 2007

2006
Advances in optimization and prediction techniques: Real-world applications.
AI Commun., 2006

2003
Influence of kNN-Based Load Forecasting Errors on Optimal Energy Production.
Proceedings of the Progress in Artificial Intelligence, 2003

Time-Series Prediction: Application to the Short-Term Electric Energy Demand.
Proceedings of the Current Topics in Artificial Intelligence, 2003

Application of Evolutionary Computation Techniques to the Optimal Short-Term Scheduling of the Electrical Energy Production.
Proceedings of the Current Topics in Artificial Intelligence, 2003

2002
A Comparison of Two Techniques for Next-Day Electricity Price Forecasting.
Proceedings of the Intelligent Data Engineering and Automated Learning, 2002

Electricity Market Price Forecasting: Neural Networks versus Weighted-Distance k Nearest Neighbours.
Proceedings of the Database and Expert Systems Applications, 13th International Conference, 2002


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