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 ...