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Advances on Time Series Analysis using Elastic Measures of Similarity
(2020-07-23)
A sequence is a collection of data instances arranged in a structured manner. When this arrangement is held in the time domain, sequences are instead referred to as time series. As such, each observation in a time series ...
Kernels of Mallows Models under the Hamming Distance for solving the Quadratic Assignment Problem
(Swarm and Evolutionary Computation, 2020-07)
The Quadratic Assignment Problem (QAP) is a well-known permutation-based combinatorial optimization problem with real applications in industrial and logistics environments. Motivated by the challenge that this NP-hard ...
An efficient K-means clustering algorithm for tall data
(DATA MINING AND KNOWLEDGE DISCOVERY, 2020)
The analysis of continously larger datasets is a task of major importance in a wide variety of scientific fields. Therefore, the development of efficient and parallel algorithms to perform such an analysis is a a crucial ...
Optimization of deep learning precipitation models using categorical binary metrics
(Journal of Advances in Modeling Earth Systems, 2020)
This work introduces a methodology for optimizing neural network models using a combination of continuous and categorical binary indices in the context of precipitation forecasting. Probability of detection or false alarm ...
An adaptive neuroevolution-based hyperheuristic
(The Genetic and Evolutionary Computation Conference, 2020)
According to the No-Free-Lunch theorem, an algorithm that performs efficiently on any type of problem does not exist. In this
sense, algorithms that exploit problem-specific knowledge usually outperform more generic ...
Supervised non-parametric discretization based on Kernel density estimation
(Pattern Recognition Letters, 2019-12-19)
Nowadays, machine learning algorithms can be found in many applications where the classifiers play a key role. In this context, discretizing continuous attributes is a common step previous to classification tasks, the main ...
Soft information for localization-of-things
(Proceeding of the IEEE, 2019-11-01)
Location awareness is vital for emerging Internetof-
Things applications and opens a new era for Localizationof-
Things. This paper first reviews the classical localization
techniques based on single-value metrics, such ...
An evolutionary discretized Lambert approach for optimal long-range rendezvous considering impulse limit
(Aerospace Science and Technology, 2019-09-18)
In this paper, an approach is presented for finding the optimal long-range space rendezvous in terms of fuel and time, considering limited impulse. In this approach , the Lambert problem is expanded towards a discretized ...
Analyzing rare event, anomaly, novelty and outlier detection terms under the supervised classification framework
(Artificial Intelligence Review, 2019-09-01)
In recent years, a variety of research areas have contributed to a set of related problems with rare event, anomaly, novelty and outlier detection terms as the main actors. These multiple research areas have created a ...
Crowd-Centric Counting via Unsupervised Learning
(2019 IEEE International Conference on Communications Workshops (ICC Workshops), 2019-07-11)
Counting targets (people or things) within a moni-tored area is an important task in emerging wireless applications,including those for smart environments, safety, and security.Conventional device-free radio-based ...