Browsing by Author "Del Ser, J."
Now showing items 1-20 of 45
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An active adaptation strategy for streaming time series classification based on elastic similarity measures
Oregi, I.; Pérez, A.
; Del Ser, J.; Lozano, J.A. (2022-05-21)
In streaming time series classification problems, the goal is to predict the label associated to the most recently received observations over the stream according to a set of categorized reference patterns. In on-line ... -
An Analysis of Coalition-Competition Pricing Strategies for Multi-Operator Mobile Traffic Offloading using Bi-objective Heuristics
Consul, J.; Perfecto, C.; Del Ser, J.; Bilbao, M.N. (2017)
In a competitive market relationships between telecommuni- cations operators serving simultaneously over a certain geographical area are diverse and motivated by very different business strategies and goals. Such relationships ... -
AT-MFCGA: An Adaptive Transfer-guided Multifactorial Cellular Genetic Algorithm for Evolutionary Multitasking
Osaba, E.; Del Ser, J.; Martínez, A.D.; Lobo, J.L.; Herrera, F. (2021-09-01)
Transfer Optimization is an incipient research area dedicated to solving multiple optimization tasks simultaneously. Among the different approaches that can address this problem effectively, Evolutionary Multitasking resorts ... -
Community Detection in Networks using Bio-inspired Optimization: Latest Developments, New Results and Perspectives with a Selection of Recent Meta-Heuristics
Osaba, E.; Del Ser, J.; Camacho, D.; Nekane Bilbao, M.N.; Yange, X.-S. (2019)
Detecting groups within a set of interconnected nodes is a widely addressed prob- lem that can model a diversity of applications. Unfortunately, detecting the opti- mal partition of a network is a computationally demanding ... -
Comparative study of pheromone control heuristics in ACO algorithms for solving RCPSP problems
Gonzalez-Pardo, A.; Del Ser, J.; Camacho, D. (2017-11)
Constraint Satisfaction Problems (CSP) belong to a kind of traditional NP-hard problems with a high impact on both research and industrial domains. The goal of these problems is to find a feasible assignment for a group ... -
Cost-efficient deployment of multi-hop wireless networks over disaster areas using multi-objective meta-heuristics
Bilbao, M.N.; Del Ser, J.; Perfecto, C.; Salcedo-Sanz, S.; Portilla-Figueras, J.A. (2017-07)
Nowadays there is a global concern with the growing frequency and magnitude of natural disasters, many of them associated with climate change at a global scale. When tackled during a stringent economic era, the allocation ... -
Cost-efficient Selective Network Caching in Large-Area Vehicular Networks using Multi-objective Heuristics
Perfecto, C.; Bilbao, M.N.; Del Ser, J. (2017)
In the last decade the interest around network caching tech- niques has augmented notably for alleviating the ever-growing demand of resources by end users in mobile networks. This gained momentum stems from the fact that ... -
CURIE: a cellular automaton for concept drift detection
Lobo, J.L.; Del Ser, J.; Osaba, E.; Bifet, A.; Herrera, F. (2021-11-01)
Data stream mining extracts information from large quantities of data flowing fast and continuously (data streams). They are usually affected by changes in the data distribution, giving rise to a phenomenon referred to as ... -
A Deep Learning Approach to the Inversion of Borehole Resistivity Measurements
Shahriari, M.; Pardo, D.; Picon, A.; Galdran, A.; Del Ser, J.; Torres-Verdin, C. (2020-04)
Borehole resistivity measurements are routinely employed to measure the electrical properties of rocks penetrated by a well and to quantify the hydrocarbon pore volume of a reservoir. Depending on the degree of geometrical ... -
Detection of non-technical losses in smart meter data based on load curve profiling and time series analysis
Villar-Rodriguez, E.; Del Ser, J.; Oregui, I.; Bilbao, M.N.; Gil-Lopez, S. (2017-06)
The advent and progressive deployment of the so-called Smart Grid has unleashed a profitable portfolio of new possibilities for an efficient management of the low-voltage distribution network supported by the introduction ... -
Error Control and Loss Functions for the Deep Learning Inversion of Borehole Resistivity Measurements
Shahriari, M.; Pardo, D.; Rivera, J.A.; Torres-Verdín, C.; Picon, A.; Ossandón, S.; Calo, V.M.; Del Ser, J. (2020-11)
Deep learning (DL) is a numerical method that approximates functions. Recently, its use has become attractive for the simulation and inversion of multiple problems in computational mechanics, including the inversion of ... -
Error Control and Loss Functions for the Deep Learning Inversion of Borehole Resistivity Measurements
Shahriari, M.; Rivera, J.A.; Pardo, D.; Torres-Verdín, C.; Picon, A.; Del Ser, J.; Ossandón, S.; Calo, V.M. (2020-05)
Deep learning (DL) is a numerical method that approximates functions. Recently, its use has become attractive for the simulation and inversion of multiple problems in computational mechanics, including the inversion of ... -
Explainable Artificial Intelligence (XAI): Concepts, Taxonomies, Opportunities and Challenges toward Responsible AI
Barredo Arrieta, A.; Herrera, F.; Chatilaf, R.; Benjaminsh, R.; Molina, D.; Gil-Lopez, S.; Garcia, S.; Barbadoh, A.; Tabikg, S.; Bennetot, A.; Del Ser, J.; Díaz-Rodríguez, N. (2019)
In the last few years, Artificial Intelligence (AI) has achieved a notable momentum that, if harnessed appropriately, may deliver the best of expectations over many application sectors across the field. For this to occur ... -
Exploiting a Stimuli Encoding Scheme of Spiking Neural Networks for Stream Learning
Lobo, J.L.; Oregi, I.; Bifet, A.; Del Ser, J. (2019)
Stream data processing has gained progressive momentum with the arriving of new stream applications and big data scenarios. One of the most promising techniques in stream learn- ing is the Spiking Neural Network, and some ... -
A Feature Selection Method for Author Identification in Interactive Communications based on Supervised Learning and Language Typicality
Villar-Rodriguez, E.; Del Ser, J.; Bilbao, M.N.; Salcedo-Sanz, S. (2016)
Authorship attribution, conceived as the identification of the origin of a text be- tween different authors, has been a very active area of research in the scientific community mainly supported by advances in Natural ... -
A Grouping Harmony Search Algorithm for Assigning Resources to Users in WCDMA Mobile Networks
Aybar-Ruiz, A.; Cuadra, L.; Salcedo-Sanz, S.; Portilla-Figueras, J.A.; Del Ser, J. (2017)
This paper explores the feasibility of a particular implemen- tation of a Grouping Harmony Search (GHS) algorithm to assign re- sources (codes, aggregate capacity, power) to users in Wide-band Code Division Multiple Access ... -
A Heuristically Optimized Complex Event Processing Engine for Big Data Stream Analytics
Olabarrieta, I.; Del Ser, J.; Torre-Bastida, A.I.; Campos-Cordobes, S.; Laña, I. (2017)
This paper describes a Big Data stream analytics platform developed within the DEWI project for processing upcoming events from wireless sensors installed in a truck. The platform consists of a Complex Event Processing ... -
Hybridizing Cartesian Genetic Programming and Harmony Search for Adaptive Feature Construction in Supervised Learning Problems
Elola, A.; Del Ser, J.; Bilbao, M.; Perfecto, C.; Alexandre , E.; Salcedo-Sanz, S. (2017-02-28)
The advent of the so-called Big Data paradigm has motivated a flurry of research aimed at enhancing machine learning models by following very di- verse approaches. In this context this work focuses on the automatic con- ... -
Intelligent Embedded Vision for Summarization of Multi-View Videos in IIoT
C. de Albuquerque, V.H.; Wook Baik, S.; Del Ser, J.; Muhammad, K.; Hussain, T. (2019)
Nowadays, video sensors are used on a large scale for various applications including security monitoring and smart transportation. However, the limited communication bandwidth and storage constraints make it challenging ... -
Intelligent SPARQL Endpoints: Optimizing Execution Performance by Automatic Query Relaxation and Queue Scheduling
Villar-Rodriguez, E.; Bilbao, M.N.; Del Ser, J.; Torre-Bastida, A.I. (2016)
The Web of Data is widely considered as one of the major global repositories populated with countless interconnected and struc- tured data prompting these linked datasets to be continuously and sharply increasing. In this ...