Francisco Martínez-Álvarez

发表

Improving Time Series Forecasting by Discovering Frequent Episodes in Sequences

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

Using Remote Data Mining on LIDAR and Imagery Fusion Data to Develop Land Cover Maps

José Cristóbal Riquelme Santos, Francisco Martínez-Álvarez, Jorge García-Gutiérrez, 2010, IEA/AIE.

Recent Advances in Energy Time Series Forecasting

Francisco Martínez-Álvarez, Alicia Troncoso, José C. Riquelme, 2017 .

A sensitivity study of seismicity indicators in supervised learning to improve earthquake prediction

Francisco Martínez-Álvarez, Gualberto Asencio-Cortés, Antonio Morales-Esteban, 2016, Knowl. Based Syst..

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..

Seismic indicators based earthquake predictor system using Genetic Programming and AdaBoost classification

Francisco Martínez-Álvarez, Khawaja M. Asim, Adnan Idris, 2018, Soil Dynamics and Earthquake Engineering.

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

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

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

Francisco Martínez-Álvarez, Alicia Troncoso, José C. Riquelme, 2015 .

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.

Short Term Earthquake Prediction in Hindukush Region Using Tree Based Ensemble Learning

Francisco Martínez-Álvarez, Khawaja M. Asim, Adnan Idris, 2016, 2016 International Conference on Frontiers of Information Technology (FIT).

TriGen: A genetic algorithm to mine triclusters in temporal gene expression data

José Cristóbal Riquelme Santos, Francisco Martínez-Álvarez, Cristina Rubio-Escudero, 2014, Neurocomputing.

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 novel tree-based algorithm to discover seismic patterns in earthquake catalogs

Francisco Martínez-Álvarez, Gualberto Asencio-Cortés, José Luis Aznarte, 2018, Comput. Geosci..

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.

Seismicity analysis and machine learning models for short-term low magnitude seismic activity predictions in Cyprus

Francisco Martínez-Álvarez, Iftikhar Azim Niaz, Khawaja M. Asim, 2020 .

Scalable Forecasting Techniques Applied to Big Electricity Time Series

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

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.

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..

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.

On the performance of deep learning models for time series classification in streaming pdf

José Cristóbal Riquelme Santos, Francisco Martínez-Álvarez, Pedro Lara-Benítez, 2020, SOCO.

On the use of algorithms to discover motifs in DNA sequences

José Cristóbal Riquelme Santos, Francisco Martínez-Álvarez, Cristina Rubio-Escudero, 2011, 2011 11th International Conference on Intelligent Systems Design and Applications.

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).

Big Data Analytics for Discovering Electricity Consumption Patterns in Smart Cities

Francisco Martínez-Álvarez, Alicia Troncoso, José C. Riquelme, 2018 .

Pattern sequence analysis to forecast time series

Francisco Martínez-Álvarez, 2010 .

Determining the best set of seismicity indicators to predict earthquakes. Two case studies: Chile and the Iberian Peninsula

Francisco Martínez-Álvarez, Antonio Morales-Esteban, Jorge Reyes, 2013, Knowl. Based Syst..

Data Science and Big Data in Energy Forecasting

Francisco Martínez-Álvarez, Alicia Troncoso, José C. Riquelme, 2018 .

Detecting precursory patterns to enhance earthquake prediction in Chile

Francisco Martínez-Álvarez, Antonio Morales-Esteban, Jorge Reyes, 2015, Comput. Geosci..

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.

A novel approach to forecast urban surface-level ozone considering heterogeneous locations and limited information

José Cristóbal Riquelme Santos, Francisco Martínez-Álvarez, Gualberto Asencio-Cortés, 2018, Environ. Model. Softw..

Obtaining optimal quality measures for quantitative association rules

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

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..

Mapping of seismic parameters of the Iberian Peninsula by means of a geographic information system

Francisco Martínez-Álvarez, Antonio Morales-Esteban, José L. Amaro-Mellado, 2018, Central Eur. J. Oper. Res..

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.

Temporal analysis of croatian seismogenic zones to improve earthquake magnitude prediction

Rudolf Scitovski, Francisco Martínez-Álvarez, Gualberto Asencio-Cortés, 2017, Earth Science Informatics.

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

Francisco Martínez-Álvarez, Alicia Troncoso, Francisco Javier Duque-Pintor, 2016 .

Hybridizing Deep Learning and Neuroevolution: Application to the Spanish Short-Term Electric Energy Consumption Forecasting

Federico Divina, Francisco Martínez-Álvarez, Alicia Troncoso, 2020, Applied Sciences.

A fast partitioning algorithm using adaptive Mahalanobis clustering with application to seismic zoning

Rudolf Scitovski, Francisco Martínez-Álvarez, Antonio Morales-Esteban, 2014, Comput. Geosci..

Classification of Gene Expression Profiles: Comparison of K-means and Expectation Maximization Algorithms

Rocío Romero-Záliz, Francisco Martínez-Álvarez, Igor Zwir, 2008, 2008 Eighth International Conference on Hybrid Intelligent Systems.

Pattern Recognition in Biological Time Series

Jesús S. Aguilar-Ruiz, Francisco Martínez-Álvarez, Carlos D. Barranco, 2011, CAEPIA.

A Novel Ensemble Method for Electric Vehicle Power Consumption Forecasting: Application to the Spanish System

Francisco Martínez-Álvarez, Alicia Troncoso, José C. Riquelme, 2019, IEEE Access.

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.

Learning analytics for student modeling in virtual reality training systems: Lineworkers case

María-Blanca Ibáñez-Espiga, Francisco Martínez-Álvarez, Gustavo Arroyo-Figueroa, 2020, Comput. Educ..

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).

Probabilistic method to select calculation accelerograms based on uniform seismic hazard acceleration response spectra

José Miguel Azañón, Francisco Martínez-Álvarez, Antonio Morales-Esteban, 2012 .

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.

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

Francisco Martínez-Álvarez, Alicia Troncoso, Gualberto Asencio-Cortés, 2017 .

A novel hybrid GA–PSO framework for mining quantitative association rules

Francisco Martínez-Álvarez, Abdorrahman Haeri, Fateme Moslehi, 2020, Soft Comput..

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..

A novel ensemble modeling approach for the spatial prediction of tropical forest fire susceptibility using LogitBoost machine learning classifier and multi-source geospatial data

Francisco Martínez-Álvarez, Farzin Shabani, Dieu Tien Bui, 2018, Theoretical and Applied Climatology.

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).

Earthquake prediction model using support vector regressor and hybrid neural networks

Francisco Martínez-Álvarez, Khawaja M. Asim, Talat Iqbal, 2018, PloS one.

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

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

Analysis of the Impact of Residential Property and Equipment on Building Energy Efficiency and Consumption—A Data Mining Approach

Francisco Martínez-Álvarez, Abdorrahman Haeri, Mahsa Nazeriye, 2020, Applied Sciences.

Discovering Spatio-Temporal Patterns in Precision Agriculture Based on Triclustering

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

Neural networks to predict earthquakes in Chile

Francisco Martínez-Álvarez, Antonio Morales-Esteban, Jorge Reyes, 2013, Appl. Soft Comput..

Using principal component analysis to improve earthquake magnitude prediction in Japan

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

Big data and natural disasters: New approaches for spatial and temporal massive data analysis

Francisco Martínez-Álvarez, Antonio Morales-Esteban, F. Martínez-Álvarez, 2019, Comput. Geosci..

SmartFD: A Real Big Data Application for Electrical Fraud Detection

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

Deep Learning for Time Series Forecasting: A Survey

Francisco Martínez-Álvarez, Alicia Troncoso, Abderrazak Sebaa, 2020, Big Data.

Mining Quantitative Association Rules in Microarray Data using Evolutive Algorithms

José Cristóbal Riquelme Santos, Francisco Martínez-Álvarez, Cristina Rubio-Escudero, 2011, ICAART.

ra A Sensitivity Analysis for Quality Measures of Quantitative Association Rules

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

A Novel Hybrid Algorithm to Forecast Functional Time Series Based on Pattern Sequence Similarity with Application to Electricity Demand

Julien Jacques, Francisco Martínez-Álvarez, Gualberto Asencio-Cortés, 2018, Energies.

A Novel Method for Seismogenic Zoning Based on Triclustering: Application to the Iberian Peninsula

Francisco Martínez-Álvarez, Antonio Morales-Esteban, Jorge Reyes, 2015, Entropy.

Analysis of Student Achievement Scores: A Machine Learning Approach

Federico Divina, Francisco Martínez-Álvarez, Miguel García-Torres, 2019, CISIS-ICEUTE.

Earthquake magnitude prediction based on artificial neural networks: A survey

Francisco Martínez-Álvarez, Antonio Morales-Esteban, José Luis Aznarte, 2016 .

Use of IT in Project-Based Learning Applied to the Subject Surveying in Civil Engineering

Francisco Martínez-Álvarez, José Lázaro Amaro-Mellado, Oihana Mitxelena-Hoyos, 2020 .

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.

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.

Game-Based Student Response System Applied to a Multidisciplinary Teaching Context

Francisco Martínez-Álvarez, Daniel Antón, José Lázaro Amaro-Mellado, 2019, CISIS-ICEUTE.

Pattern recognition to forecast seismic time series

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

Hybrid Artificial Intelligent Systems: 11th International Conference, HAIS 2016, Seville, Spain, April 18-20, 2016, Proceedings

Héctor Quintián, Francisco Martínez-Álvarez, Alicia Troncoso, 2016 .

Advanced Machine Learning and Big Data Analytics in Remote Sensing for Natural Hazards Management

Francisco Martínez-Álvarez, Dieu Tien Bui, D. Bui, 2020, Remote. Sens..

A Preliminary Study on Deep Transfer Learning Applied to Image Classification for Small Datasets

José Cristóbal Riquelme Santos, Francisco Martínez-Álvarez, Gualberto Asencio-Cortés, 2020, SOCO.

Earthquake prediction in California using regression algorithms and cloud-based big data infrastructure

Francisco Martínez-Álvarez, Gualberto Asencio-Cortés, Antonio Morales-Esteban, 2017, Comput. Geosci..

Finding Electric Energy Consumption Patterns in Big Time Series Data

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

Passivity Based Control of Cyber Physical Systems Under Zero-Dynamics Attack

Naeem Iqbal, Francisco Martínez-Álvarez, Khawaja M. Asim, 2016, HAIS.

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.

Hybrid Artificial Intelligent Systems

Emilio Corchado, Héctor Quintián, Francisco Martínez-Álvarez, 2016, Lecture Notes in Computer Science.

A novel imputation methodology for time series based on pattern sequence forecasting

Kishore Kulat, Francisco Martínez-Álvarez, Neeraj Bokde, 2018, Pattern Recognit. Lett..

A novel deep learning neural network approach for predicting flash flood susceptibility: A case study at a high frequency tropical storm area.

Pijush Samui, Nhat-Duc Hoang, Romulus Costache, 2019, The Science of the total environment.

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

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

Clustering preprocessing to improve time series forecasting

Francisco Martínez-Álvarez, 2011, AI Commun..

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.

Medium-Term Electricity Consumption Forecasting in Algeria Based on Clustering, Deep Learning and Bayesian Optimization Methods

Francisco Martínez-Álvarez, Abderrazak Sebaa, Dalil Hadjout, 2021, SOCO.

Modules and the Data Sets

Kristian Sabo, Rudolf Scitovski, Francisco Martínez-Álvarez, 2021, Cluster Analysis and Applications.

Mahalanobis clustering for the determination of incidence-magnitude seismic parameters for the Iberian Peninsula and the Republic of Croatia

Rudolf Scitovski, Francisco Martínez-Álvarez, Antonio Morales-Esteban, 2021, Comput. Geosci..

A Model-Based Deep Transfer Learning Algorithm for Phenology Forecasting Using Satellite Imagery

Francisco Martínez-Álvarez, Gualberto Asencio-Cortés, M. J. Jiménez-Navarro, 2021, HAIS.

Stability analysis of a slope subject to real accelerograms by finite elements. Application to San Pedro cliff at the Alhambra in Granada

Francisco Martínez-Álvarez, Antonio Morales-Esteban, P. Durand, 2015 .

Comparing seismic parameters for different source zone models in the Iberian Peninsula

Francisco Martínez-Álvarez, Gualberto Asencio-Cortés, Antonio Morales-Esteban, 2017 .