Now showing items 23-42 of 45

    • 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. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 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 ...
    • Learning to classify software defects from crowds: a novel approach 

      Hernández-González J.; Rodríguez D.; Inza I.; Rachel H.; Lozano J.A. (Applied Soft Computing, 2017-11-01)
      In software engineering, associating each reported defect with a cate- gory allows, among many other things, for the appropriate allocation of resources. Although this classification task can be automated using stan- dard ...
    • Mallows and generalized Mallows model for matchings 

      Irurozki E.; Calvo B.; Lozano J.A. (Bernoulli, 2019-02-25)
      The Mallows and Generalized Mallows Models are two of the most popular probability models for distribu- tions on permutations. In this paper, we consider both models under the Hamming distance. This models can be seen as ...
    • Measuring the Class-imbalance Extent of Multi-class Problems 

      Ortigosa-Hernández J.; Inza I.; Lozano J.A. (Pattern Recognition Letter, 2017-07-30)
      Since many important real-world classification problems involve learning from unbalanced data, the challenging class-imbalance problem has lately received con- siderable attention in the community. Most of the methodological ...
    • Multi-objective Optimization of Orbit Transfer Trajectory Using Imperialist Competitive Algorithm 

      Shirazi A. (IEEE Aerospace Conference, 2017-03-04)
      This paper proposes a systematic direct approach to carry out effective multi-objective optimization of space orbit transfer with high-level thrust acceleration. The objective is to provide a transfer trajectory with ...
    • Multi-objectivising Combinatorial Optimisation Problems by means of Elementary Landscape Decompositions 

      Ceberio J.; Calvo B.; Mendiburu A.; Lozano JA. (Evolutionary Computation, 2017-12)
      In the last decade, many works in combinatorial optimisation have shown that, due to the advances in multi-objective optimisation, the algorithms from this field could be used for solving single-objective problems as well. ...
    • Nature-inspired approaches for distance metric learning in multivariate time series classification 

      Oregui I.; Del Ser J.; Pérez A.; Lozano J.A. (IEEE Congress on Evolutionary Computation (CEC), 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 ...
    • A note on the behavior of majority voting in multi-class domains with biased annotators 

      Hernández-González J.; Inza I.; Lozano J.A. (IEEE Transactions on Knowledge and Data Engineering, 2018-05)
      Majority voting is a popular and robust strategy to aggregate different opinions in learning from crowds, where each worker labels examples ac- cording to their own criteria. Although it has been extensively studied in the ...
    • A note on the Boltzmann distribution and the linear ordering problem 

      Ceberio J.; Mendiburu A.; Lozano J.A. (Lecture Notes in Computer Science, 2016-10-01)
      The Boltzmann distribution plays a key role in the field of optimization as it directly connects this field with that of probability. Basically, given a function to optimize, the Boltzmann distribution associated to this ...
    • 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 IEEE Congress on Evolutionary Computation, CEC 2016, 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 ...
    • On the applicability of ant colony optimization to non-intrusive load monitoring in smart grids 

      Gonzalez-Pardo A.; Del Ser J.; Camacho D. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 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 ...
    • On the relevance of preprocessing in predictive maintenance for dynamic systems 

      Cernuda C. (Predictive Maintenance in Dynamic Systems, 2018)
      The complexity involved in the process of real-time data-driven monitoring dynamic systems for predicted maintenance is usually huge. With more or less in-depth any data-driven approach is sensitive to data preprocessing, ...
    • On-Line Dynamic Time Warping for Streaming Time Series 

      Oregi I.; Pérez A.; Del Ser J.; Lozano J.A. (Machine Learning and Knowledge Discovery in Databases. ECML PKDD 2017. Lecture Notes in Computer Science, 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 ...
    • An optimization tool to design the field of a Solar Power Tower plant allowing heliostats of different sizes 

      Carrizosa E.; Domínguez-Bravo C.; Fernández-Cara E.; Quero M. (International Journal of Energy Research, 2016-10-30)
      The design of a Solar Power Tower plant involves the optimization of the heliostat field layout. Fields are usually designed to have all heliostats of identical size. Although the use of a single heliostat size has been ...
    • Path Planning for Single Unmanned Aerial Vehicle by Separately Evolving Waypoints 

      Yang P.; Tang K.; Lozano J.A.; Cao X. (IEEE Transactions on Robotics, 2015-12-31)
      Evolutionary algorithm-based unmanned aerial vehicle (UAV) path planners have been extensively studied for their effectiveness and flexibility. However, they still suffer from a drawback that the high-quality waypoints in ...
    • perm mateda: A matlab toolbox of estimation of distribution algorithms for permutation-based combinatorial optimization problems 

      Irurozki E.; Ceberio J.; Santamaria J.; Santana R.; Mendiburu A. (ACM Transactions on Mathematical Software, 2018)
      Permutation problems are combinatorial optimization problems whose solutions are naturally codified as permutations. Due to their complexity, motivated principally by the factorial cardinality of the search space of ...
    • A review on distance based time series classification 

      Abanda A.; Mori U.; Lozano JA. (Data Mining and Knowledge Discovery,, 2018-11-01)
      Time series classification is an increasing research topic due to the vast amount of time series data that is being created over a wide variety of fields. The particularity of the data makes it a challenging task and ...
    • Soft range information for network localization 

      Mazuelas S.; Conti A.; Allen J.C.; Win M.Z. (IEEE Transactions on Signal Processing, 2018-06-15)
      The demand for accurate localization in complex environments continues to increase despite the difficulty in extracting positional information from measurements. Conventional range-based localization approaches rely on ...
    • Spacecraft Trajectory Optimization: A review of Models, Objectives, Approaches and Solutions 

      Shirazi A.; Ceberio J.; Lozano J.A. (Progress in Aerospace Sciences, 2018)
      This article is a survey paper on solving spacecraft trajectory optimization problems. The solving process is decomposed into four key steps of mathematical modeling of the problem, defining the objective functions, ...
    • Spatiotemporal information coupling in network navigation 

      Mazuelas S.; Shen Y.; Win Z. (IEEE Transactions on Information Theory, 2018-12)
      Network navigation, encompassing both spatial and temporal cooperation to locate mobile agents, is a key enabler for numerous emerging location-based applications. In such cooperative networks, the positional information ...