Antonio Manuel Durán-Rosal

Orcid: 0000-0003-4587-357X

According to our database1, Antonio Manuel Durán-Rosal authored at least 26 papers between 2015 and 2023.

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

Timeline

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Bibliography

2023
Generalised triangular distributions for ordinal deep learning: Novel proposal and optimisation.
Inf. Sci., November, 2023

An Evolutionary Artificial Neural Network approach for spatio-temporal wave height time series reconstruction.
Appl. Soft Comput., October, 2023

A multi-class classification model with parametrized target outputs for randomized-based feedforward neural networks.
Appl. Soft Comput., January, 2023

Gramian Angular and Markov Transition Fields Applied to Time Series Ordinal Classification.
Proceedings of the Advances in Computational Intelligence, 2023

2022
Gamifying the Classroom for the Acquisition of Skills Associated with Machine Learning: A Two-Year Case Study.
Proceedings of the International Joint Conference 15th International Conference on Computational Intelligence in Security for Information Systems (CISIS 2022) 13th International Conference on EUropean Transnational Education (ICEUTE 2022), 2022

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

A new approach for optimal offline time-series segmentation with error bound guarantee.
Pattern Recognit., 2021

2020
A new approach for optimal time-series segmentation.
Pattern Recognit. Lett., 2020

2019
Dynamical memetization in coral reef optimization algorithms for optimal time series approximation.
Prog. Artif. Intell., 2019

On the use of evolutionary time series analysis for segmenting paleoclimate data.
Neurocomputing, 2019

A hybrid dynamic exploitation barebones particle swarm optimisation algorithm for time series segmentation.
Neurocomputing, 2019

2018
Simultaneous optimisation of clustering quality and approximation error for time series segmentation.
Inf. Sci., 2018

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

A statistically-driven Coral Reef Optimization algorithm for optimal size reduction of time series.
Appl. Soft Comput., 2018

Efficient fog prediction with multi-objective evolutionary neural networks.
Appl. Soft Comput., 2018

Distribution-Based Discretisation and Ordinal Classification Applied to Wave Height Prediction.
Proceedings of the Intelligent Data Engineering and Automated Learning - IDEAL 2018, 2018

An Empirical Validation of a New Memetic CRO Algorithm for the Approximation of Time Series.
Proceedings of the Advances in Artificial Intelligence, 2018

Hybrid Weighted Barebones Exploiting Particle Swarm Optimization Algorithm for Time Series Representation.
Proceedings of the Bioinspired Optimization Methods and Their Applications, 2018

2017
Identification of extreme wave heights with an evolutionary algorithm in combination with a likelihood-based segmentation.
Prog. Artif. Intell., 2017

Identifying Market Behaviours Using European Stock Index Time Series by a Hybrid Segmentation Algorithm.
Neural Process. Lett., 2017

A Coral Reef Optimization Algorithm for Wave Height Time Series Segmentation Problems.
Proceedings of the Advances in Computational Intelligence, 2017

2016
Hybridization of neural network models for the prediction of Extreme Significant Wave Height segments.
Proceedings of the 2016 IEEE Symposium Series on Computational Intelligence, 2016

Time Series Representation by a Novel Hybrid Segmentation Algorithm.
Proceedings of the Hybrid Artificial Intelligent Systems - 11th International Conference, 2016

On the Use of the Beta Distribution for a Hybrid Time Series Segmentation Algorithm.
Proceedings of the Advances in Artificial Intelligence, 2016

Multiclass Prediction of Wind Power Ramp Events Combining Reservoir Computing and Support Vector Machines.
Proceedings of the Advances in Artificial Intelligence, 2016

2015
Applying a Hybrid Algorithm to the Segmentation of the Spanish Stock Market Index Time Series.
Proceedings of the Advances in Computational Intelligence, 2015


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