Data Science (DS)
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A system for airport weather forecasting based on circular regression trees
(Environmental Modelling & Software, 20171101)This paper describes a suite of tools and a model for improving the accuracy of airport weather forecasts produced by numerical weather prediction (NWP) products, by learning from the relationships between previously ... 
Learning to classify software defects from crowds: a novel approach
(Applied Soft Computing, 20171101)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 ... 
Correcting for spatial heterogeneity in plant breeding experiments with Psplines
(Spatial Statistics, 20171027)An important aim of the analysis of agricultural field experiments is to obtain good predictions for genotypic performance, by correcting for spatial effects. In practice these corrections turn out to be complicated, since ... 
Early classification of time series by simultaneously optimizing the accuracy and earliness
(IEEE Transactions on Neural Networks and Learning Systems, 201710)The problem of early classi cation of time series appears naturally in contexts where the data, of temporal nature, is collected over time, and early class predictions are interesting or even required. The objective is to ... 
An efficient evolutionary algorithm for the orienteering problem
(Computers and Operations Research, 20170906)This paper deals with the Orienteering Problem, which is a routing problem. In the Orienteering Problem, each node has a profit assigned and the goal is to find the route that maximizes the total collected profit subject ... 
The Weighted Independent Domination Problem: ILP Model and Algorithmic Approaches
(European Journal of Operational Research, 20170830)This work deals with the socalled weighted independent domination problem, which is an $NP$hard combinatorial optimization problem in graphs. In contrast to previous work, this paper considers the problem from a ... 
Measuring the Classimbalance Extent of Multiclass Problems
(Pattern Recognition Letter, 20170730)Since many important realworld classification problems involve learning from unbalanced data, the challenging classimbalance problem has lately received con siderable attention in the community. Most of the methodological ... 
Costefficient deployment of multihop wireless networks over disaster areas using multiobjective metaheuristics
(Neurocomputing, 201707)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 ... 
Comparative study of pheromone control heuristics in ACO algorithms for solving RCPSP problems
(Applied Soft Computing, 201711)Constraint Satisfaction Problems (CSP) belong to a kind of traditional NPhard 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 ... 
Millimeter Wave V2V Communications: Distributed Association and Beam Alignment
(IEEE Journal on Selected Areas in Communications, 2017)Recently millimeterwave 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 ... 
Underwater Robot Task Planning Using MultiObjective MetaHeuristics
(Sensors, 201704)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 ... 
A novel Fireworks Algorithm with wind inertia dynamics and its application to traffic forecasting
(IEEE Congress on Evolutionary Computation, 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 ... 
Natureinspired approaches for distance metric learning in multivariate time series classification
(IEEE Congress on Evolutionary Computation, 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 ... 
Multiobjective heuristics applied to robot task planning for inspection plants
(IEEE Congress on Evolutionary Computation, 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 socalled ... 
Natureinspired heuristics for the multiplevehicle selective pickup and delivery problem under maximum profit and incentive fairness criteria
(IEEE Congress on Evolutionary Computation, 2017)This work focuses on widescale freight transportation logistics motivated by the sharp increase of online shopping stores and the upsurge of Internet as the most frequently utilized selling channel during the last decade. ... 
A local search method for graph clustering heuristics based on partitional distribution learning
(IEEE Congress on Evolutionary Computation, 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, ... 
KETpicMatlab Toolbox for LaTeX HighQuality Graphical Artwork in Educational Materials on Bézier Curve Algorithms at a Master Level
(Lecture Notes in Computer Science, 201707)This paper introduces a new toolbox to generate highquality 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 ... 
A simple Bayesian linear excess relative risk model
(20170711)A new Bayesian Poisson relative risk model is proposed for displaying the excess relative risk associated to a unique exposure as a probability distribution in a closed form. The background risk can be modelled by a unique ... 
Detection of nontechnical losses in smart meter data based on load curve profiling and time series analysis
(Energy, 201706)The advent and progressive deployment of the socalled Smart Grid has unleashed a profitable portfolio of new possibilities for an efficient management of the lowvoltage distribution network supported by the introduction ... 
The weighted independent domination problem: ILP model and algorithmic approaches
(Lecture Notes in Computer Science, 20170601)This work deals with the socalled weighted independent domination problem, which is an N P hard combinatorial optimization problem in graphs. In contrast to previous theoretical work from the liter ature, this paper ...