247 citations · 392 across the 14 of their papers we have counts for
15 papers
Extended Weighted ABG: A Robust Non-Linear ABG-Based Approach for Optimal Combination of ABG Path-Loss Propagation Models
David. Casillas-Pérez, Daniel. Merino-Pérez, Silvia. Jiménez-Fernández +2
This paper proposes a robust non-linear generalized path-loss propagation model, the Extended Weighted ABG (EWABG), which efficiently allows generating a path-loss propagation mode…
Evolutionary optimization of spatially-distributed multi-sensors placement for indoor surveillance environments with security levels
Luis M. Moreno-Saavedra, Vinıcius G. Costa, Adrian Garrido-Saez +3
The surveillance multisensor placement is an important optimization problem that consists of positioning several sensors of different types to maximize the coverage of a determined…
A multi-algorithm approach for operational human resources workload balancing in a last mile urban delivery system
Luis M. Moreno-Saavedra, Silvia Jimenez-Fernandez, Antonio Portilla-Figueras +2
Efficient workload assignment to the workforce is critical in last-mile package delivery systems. In this context, traditional methods of assigning package deliveries to workers ba…
CoSeNet: A Novel Approach for Optimal Segmentation of Correlation Matrices
Alberto. Palomo-Alonso, David Casillas-Perez, Silvia Jimenez-Fernandez +2
In this paper, we propose a novel approach for the optimal identification of correlated segments in noisy correlation matrices. The proposed model is known as CoSeNet (Correlation…
Structures vibration control via tuned mass dampers using a co-evolution coral reefs optimization algorithm
S Salcedo-Sanz, C Camacho-Gómez, A Magdaleno +2
In this paper we tackle a problem of optimal design and location of Tuned Mass Dampers (TMDs) for structures subjected to earthquake ground motions, using a novel meta-heuristic al…
A comprehensive review of visualization methods for association rule mining: Taxonomy, Challenges, Open problems and Future ideas
Iztok Fister, Dušan Fister, Vili Podgorelec +1
Association rule mining is intended for searching for the relationships between attributes in transaction databases. The whole process of rule discovery is very complex, and involv…
Time series numerical association rule mining variants in smart agriculture
Iztok Fister, Dušan Fister, Vili Podgorelec +1
Numerical association rule mining offers a very efficient way of mining association rules, where algorithms can operate directly with categorical and numerical attributes. These me…
New Probabilistic-Dynamic Multi-Method Ensembles for Optimization based on the CRO-SL
Jorge Pérez-Aracil, Carlos Camacho-Gómez, Eugenio Lorente-Ramos +2
In this paper we propose new probabilistic and dynamic (adaptive) strategies to create multi-method ensembles based on the Coral Reefs Optimization with Substrate Layers (CRO-SL) a…
Accurate Long-term Air Temperature Prediction with a Fusion of Artificial Intelligence and Data Reduction Techniques
Dušan Fister, Jorge Pérez-Aracil, César Peláez-Rodríguez +2
In this paper three customised Artificial Intelligence (AI) frameworks, considering Deep Learning (convolutional neural networks), Machine Learning algorithms and data reduction te…
Analysis, Characterization, Prediction and Attribution of Extreme Atmospheric Events with Machine Learning: a Review
Sancho Salcedo-Sanz, Jorge Pérez-Aracil, Guido Ascenso +9
Atmospheric Extreme Events (EEs) cause severe damages to human societies and ecosystems. The frequency and intensity of EEs and other associated events are increasing in the curren…
Persistence in Complex Systems
S. Salcedo-Sanz, D. Casillas-Pérez, J. Del Ser +4
Persistence is an important characteristic of many complex systems in nature, related to how long the system remains at a certain state before changing to a different one. The stud…
An Efficient Multi-objective Evolutionary Approach for Solving the Operation of Multi-Reservoir System Scheduling in Hydro-Power Plants
C. G. Marcelino, G. M. C. Leite, C. A. D. M Delgado +4
This paper tackles the short-term hydro-power unit commitment problem in a multi-reservoir system - a cascade-based operation scenario. For this, we propose a new mathematical mode…
Randomization-based Machine Learning in Renewable Energy Prediction Problems: Critical Literature Review, New Results and Perspectives
Javier Del Ser, David Casillas-Perez, Laura Cornejo-Bueno +4
Randomization-based Machine Learning methods for prediction are currently a hot topic in Artificial Intelligence, due to their excellent performance in many prediction problems, wi…
Machine Learning Information Fusion in Earth Observation: A Comprehensive Review of Methods, Applications and Data Sources
S. Salcedo-Sanz, P. Ghamisi, M. Piles +7
This paper reviews the most important information fusion data-driven algorithms based on Machine Learning (ML) techniques for problems in Earth observation. Nowadays we observe and…
A mixture of experts model for predicting persistent weather patterns
Maria Perez-Ortiz, Pedro A. Gutierrez, Peter Tino +2
Weather and atmospheric patterns are often persistent. The simplest weather forecasting method is the so-called persistence model, which assumes that the future state of a system w…