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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 ...
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Rank aggregation for non-stationary data streams
Irurozki, E.; Pérez, A.; Lobo, J.L.; Del Ser, J. (2022)
The problem of learning over non-stationary ranking streams arises naturally, particularly in recommender systems. The rankings represent the preferences of a population, and the non-stationarity means that the distribution ...
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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 ...
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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 ...
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LUNAR: Cellular automata for drifting data streams
Lobo, J.L.; Del Ser, J.; Herrera, F. (2021-01-08)
With the advent of fast data streams, real-time machine learning has become a challenging task, demanding many processing resources. In addition, they can be affected by the concept drift effect, by which learning methods ...
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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 ...
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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 ...
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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 ...
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jMetalPy: a Python Framework for Multi-Objective Optimization with Metaheuristics
Del Ser, J.; Benítez-Hidalgo, A.; J. Nebro, A.; García-Nieto, J.; Oregi, I. (2019-10-31)
This paper describes jMetalPy, an object-oriented Python-based framework for multi-objective optimization with metaheuristic techniques. Building upon our experiences with the well-known jMetal framework, we have developed ...
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On-line Elastic Similarity Measures for time series
Oregui, I.; Pérez, A.; Del Ser, J.; Lozano, J.A. (2019-04)
The way similarity is measured among time series is of paramount importance in many data mining and machine learning tasks. For instance, Elastic Similarity Measures are widely used to determine whether two time series are ...
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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 ...
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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 ...
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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 ...
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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 ...
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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 ...
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On-Line Dynamic Time Warping for Streaming Time Series
Oregui, I.; Pérez, A.; Del Ser, J.; Lozano, J.A. (2017-09)
Dynamic Time Warping is a well-known measure of dissimilarity between time series. Due to its flexibility to deal with non-linear distortions along the time axis, this measure has been widely utilized in machine learning ...
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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 ...
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KETpic-Matlab Toolbox for LaTeX High-Quality Graphical Artwork in Educational Materials on Bézier Curve Algorithms at a Master Level
Gálvez, A.; Takato, S.; Kaneko, M.; Del Ser, J.; Iglesias, A. (2017-07)
This paper introduces a new toolbox to generate high-quality graphical artwork about the main algorithms for Bézier curves and related topics. The package has been implemented by the authors as a supporting middleware tool ...
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Nature-inspired approaches for distance metric learning in multivariate time series classification
Oregui, I.; Del Ser, J.; Pérez, A.; Lozano, J.A. (2017-07)
The applicability of time series data mining in many different fields has motivated the scientific community to focus on the development of new methods towards improving the performance of the classifiers over this particular ...
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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 ...
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Underwater Robot Task Planning Using Multi-Objective Meta-Heuristics
Landa-Torres, I.; Manjarres, D.; Bilbao, S.; Del Ser, J. (2017-04)
Robotics deployed in the underwater medium are subject to stringent operational conditions that impose a high degree of criticality on the allocation of resources and the schedule of operations in mission planning. In this ...
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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- ...
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A Novel Grouping Harmony Search Algorithm for Clustering Problems
Landa-Torres, I.; Del Ser, J.; Manjarres, D.; Gil-Lopez, S.; Salcedo-Sanz, S. (2017)
The problem of partitioning a data set into disjoint groups or clusters of related items plays a key role in data analytics, in particular when the information retrieval becomes crucial for further data analysis. In this ...
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Joint Feature Selection and Parameter Tuning for Short-term Traffic Flow Forecasting based on Heuristically Optimized Multi-layer Neural Networks
Oregi, I.; Del Ser, J.; Laña, I.; Vélez, M. (2017)
Short-term traffic flow forecasting is a vibrant research topic that has been growing in interest since the late 70’s. In the last decade this vibrant field has shifted its focus towards machine learning methods. These ...
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On the Interplay between Scheduling Interval and Beamwidth Selection for Low-Latency and Reliable V2V mmWave Communications
Perfecto, C.; Del Ser, J.; Bennis, M. (2017)
The interest in mmWave communications has risen sharply in the last years motivated by their widespread con- sideration as a technological solution capable of dealing with the stringent rate requirements currently demanded ...
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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 ...
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On the Creation of Diverse Ensembles for Nonstationary Environments using Bio-inspired Heuristics
Lobo, J.L.; Del Ser, J.; Villar-Rodriguez, E.; Salcedo-Sanz, S.; Bilbao, M.N. (2017)
Recently the relevance of adaptive models for dynamic data environments has turned into a hot topic due to the vast number of sce- narios generating nonstationary data streams. When a change (concept drift) in data ...
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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 ...
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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 ...
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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 ...
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Quantitative Analysis and Performance Study of Ant Colony Optimization Models Applied to Multi-Mode Resource Constraint Project Scheduling Problem
Gonzalez-Pardo, A.; Del Ser, J.; Camacho, D. (2017)
Constraint Satisfaction Problems (CSP) belongs to this kind of traditional NP-hard problems with a high impact in both, research and industrial domains. However, due to the complexity that CSP problems exhibit, researchers ...
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Multi-objective heuristics applied to robot task planning for inspection plants
Landa-Torres, I.; Lobo, J.L.; Murua, I.; Manjarres, D.; Del Ser, J. (2017)
Robotics are generally subject to stringent operational conditions that impose a high degree of criticality on the allocation of resources and the schedule of operations in mission planning. In this regard the so-called ...
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Optimal Phase Swapping in Low Voltage Distribution Networks based on Smart Meter Data and Optimization Heuristics
Mendia, I.; Gil-Lopez, S.; Del Ser, J.; Gonzalez, A.; García, J.; Vélez, M. (2017)
In this paper a modified version of the Harmony Search al- gorithm is proposed as a novel tool for phase swapping in Low Voltage Distribution Networks where the objective is to determine to which phase each load should be ...
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Wireless Network Optimization for Massive V2I Data Collection using Multiobjective Harmony Search Heuristics
Sobron, I.; Alonso, B.; Del Ser, J.; Vélez, M. (2017)
This paper proposes to improve the efficiency of the deploy- ment of wireless network infrastructure for massive data collection from vehicles over regional areas. The increase in the devices that are carried by vehicles ...
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Nature-inspired approaches for distance metric learning in multivariate time series classification
Oregui, I.; Del Ser, J.; Pérez, A.; Lozano, J.A. (2017)
The applicability of time series data mining in many different fields has motivated the scientific community to focus on the development of new methods towards improving the performance of the classifiers over this particular ...
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Millimeter Wave V2V Communications: Distributed Association and Beam Alignment
Perfecto, C.; Del Ser, J.; Bennis, M. (2017)
Recently millimeter-wave bands have been postulated as a means to accommodate the foreseen extreme bandwidth demands in vehicular communications, which result from the dissemination of sensory data to nearby vehicles for ...
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Nature-inspired heuristics for the multiple-vehicle selective pickup and delivery problem under maximum profit and incentive fairness criteria
Del Ser, J.; Torre-Bastida, A.I.; Laña, I.; Bilbao, M.N.; Perfecto, C. (2017)
This work focuses on wide-scale freight transportation logistics motivated by the sharp increase of on-line shopping stores and the upsurge of Internet as the most frequently utilized selling channel during the last decade. ...
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A novel Fireworks Algorithm with wind inertia dynamics and its application to traffic forecasting
Laña, I.; Del Ser, J.; Vélez, M. (2017)
Fireworks Algorithm (FWA) is a recently contributed heuristic optimization method that has shown a promising performance in applications stemming from different domains. Improvements to the original algorithm have been ...
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A local search method for graph clustering heuristics based on partitional distribution learning
Manjarres, D.; Landa-Torres, I.; Del Ser, J. (2017)
The community structure of complex networks reveals hidden relationships in the organization of their constituent nodes. Indeed, many practical problems stemming from different fields of knowledge such as Biology, Sociology, ...
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A novel adaptive density-based ACO algorithm with minimal encoding redundancy for clustering problems
Villar-Rodriguez, E.; Gonzalez-Pardo, A.; Del Ser, J.; Bilbao, M.N.; Salcedo-Sanz, S. (2016-11-14)
In the so-called Big Data paradigm descriptive analytics are widely conceived as techniques and models aimed at discovering knowledge within unlabeled datasets (e.g. patterns, similarities, etc) of utmost help for subsequent ...
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Joint topology optimization, power control and spectrum allocation for intra-vehicular multi-hop sensor networks using dandelion-encoded heuristics
Del Ser, J.; Bilbao, M.N.; Perfecto, C.; Gonzalez-Pardo, A.; Campos-Cordobes, S. (2016-01-01)
In the last years the interest in multi-hop communications has gained momentum within the research community due to the challenging characteristics of the intra-vehicular radio environment and the stringent robustness ...
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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 ...
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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 ...
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The Role of Local Urban Traffic and Meteorological Conditions in Air Pollution: A Data-based Case Study in Madrid, Spainc
Laña, I.; Del Ser, J.; Padró, A.; Vélez, M.; Casanova-Mateo, C. (2016)
Urban air pollution is a matter of growing concern for both public adminis- trations and citizens. Road traffic is one of the main sources of air pollutants, though topography characteristics and meteorological conditions ...
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On the applicability of ant colony optimization to non-intrusive load monitoring in smart grids
Gonzalez-Pardo, A.; Del Ser, J.; Camacho, D. (2015-12-31)
Along with the proliferation of the Smart Grid, power load disaggregation is a research area that is lately gaining a lot of popularity due to the interest of energy distribution companies and customers in identifying ...