Listar1. Investigación por tema "Clustering"
Mostrando ítems 1-20 de 20
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A Hybrid Intelligent Modeling approach for predicting the solar thermal panel energy production
(Elsevier, 2024-01-14)[Abstract] There is no doubt that the European Union is undergoing an ecological transition, with renewable energies accounting for an increasing share of energy consumption in the Member States. In Spain, solar energy is ... -
A Hybrid Intelligent System to Forecast Solar Energy Production
(Elsevier, 2019-08-07)[Abstarct]: There is wide acknowledgement that solar energy is a promising and renewable source of electricity. However, complementary sources are sometimes required, due to its limited capacity, in order to satisfy user ... -
A hybrid one-class approach for detecting anomalies in industrial systems
(John Wiley & Sons Ltd, 2022-03-08)[Abstract]: The significant advance of Internet of Things in industrial environments has provided the possibility of monitoring the different variables that come into play in an industrial process. This circumstance allows ... -
Application of Machine Learning in the Identification and Prediction of Maritime Accident Factors
(MDPI, 2024)[Abstract] Artificial intelligence seems to be a new point of view to classical problems that, in the past, could not be understood in depth, leaving certain gaps in each knowledge area. As an example of this, maritime ... -
Automatic group-wise whole-brain short association fiber bundle labeling based on clustering and cortical surface information
(BioMed Central Ltd., 2020-06-03)[Abstract] Background Diffusion MRI is the preferred non-invasive in vivo modality for the study of brain white matter connections. Tractography datasets contain 3D streamlines that can be analyzed to study the main ... -
Beta-Hebbian Learning to enhance unsupervised exploratory visualizations of Android malware families
(Oxford University Press, 2024-05-20)[Abstract] As it is well known, mobile phones have become a basic gadget for any individual that usually stores sensitive information. This mainly motivates the increase in the number of attacks aimed at jeopardizing ... -
Bio-inspired model of ground temperature behavior on the horizontal geothermal exchanger of an installation based on a heat pump
(Elsevier, 2015-02-20)[Abstract] Nowadays the Heat Pump is one of the best systems to warm a building with a good performance. Usually, with the aim to increase the efficiency, a geothermal heat exchanger is added to the installation. This ... -
CABRA: Clustering algorithm based on regular arrangement
(Elsevier, 2024)[Abstract]: Clustering is an unsupervised learning technique for organizing complex datasets into coherent groups. A novel clustering algorithm is presented, with a simple grouping concept depending on only one hyperparameter, ... -
Do all roads lead to Rome? Studying distance measures in the context of machine learning
(Elsevier Ltd, 2023-09)[Abstract]: Many machine learning and data mining tasks are based on distance measures, so a large amount of literature addresses this aspect somehow. Due to the broad scope of the topic, this paper aims to provide an ... -
Electromyogram prediction during anesthesia by using a hybrid intelligent model
(Springer Nature, 2019-08-23)[Abstract] In the search for new and more efficient ways to administer drugs, clinicians are turning to engineering tools. The availability of these models to predict physiological variables are a significant factor. A ... -
Hybrid Intelligent Modelling in Renewable Energy Sources-Based Microgrid. A Variable Estimation of the Hydrogen Subsystem Oriented to the Energy Management Strategy
(MDPI, 2020)[Abstract] This work deals with the prediction of variables for a hydrogen energy storage system integrated into a microgrid. Due to the fact that this kind of system has a nonlinear behaviour, the use of traditional ... -
Hybrid Intelligent System to Perform Fault Detection on BIS Sensor During Surgeries
(Multidisciplinary Digital Publishing Institute, 2017)This paper presents a new fault detection system in hypnotic sensors used for general anesthesia during surgery. Drug infusion during surgery is based on information received from patient monitoring devices; accordingly, ... -
Machine learning for multivariate time series with the R package mlmts
(Elsevier B.V., 2023-06)[Abstract]: Time series data are ubiquitous nowadays. Whereas most of the literature on the topic deals with univariate time series, multivariate time series have typically received much less attention. However, the ... -
New Climatic Indicators for Improving Urban Sprawl: A Case Study of Tehran City
(Multidisciplinary Digital Publishing Institute, 2013)In the modern world, the fine balance and delicate relationship between human society and the environment in which we exist has been affected by the phenomena of urbanisation and urban development. Today, various environmental ... -
Quantile Cross-Spectral Density: A Novel and Effective Tool for Clustering Multivariate Time Series
(Elsevier, 2021)[Abstract] Clustering of multivariate time series is a central problem in data mining with applications in many fields. Frequently, the clustering target is to identify groups of series generated by the same multivariate ... -
Quantile-Based Fuzzy Clustering of Multivariate Time Series in the Frequency Domain
(Elsevier, 2022)[Abstract] A novel procedure to perform fuzzy clustering of multivariate time series generated from different dependence models is proposed. Different amounts of dissimilarity between the generating models or changes on ... -
Servet: A Benchmark Suite for Autotuning on Multicore Clusters
(Institute of Electrical and Electronics Engineers, 2010-05-24)[Abstract] MapReduce is a powerful tool for processing large data sets used by many applications running in distributed environments. However, despite the increasing number of computationally intensive problems that require ... -
Solar thermal collector output temperature prediction by hybrid intelligent model for smartgrid and smartbuildings applications and optimization
(MDPI, 2020-07-05)[Abstract] Currently, there is great interest in reducing the consumption of fossil fuels (and other non-renewable energy sources) in order to preserve the environment; smart buildings are commonly proposed for this purpose ... -
The linear model of an unknown dynamic process
(CIMNE, Barcelona, 1998)[Abstract] This work describes a novel algorithmic approach to find the linear model of any dynamic process. Dynamic behaviour as a knowledge concept is acquired by means of proposed learning algorithm, being supported by ... -
Unsupervised Classification of Categorical Time Series Through Innovative Distances
(Springer Science and Business Media Deutschland GmbH, 2023)[Abstract]: In this paper, two novel distances for nominal time series are introduced. Both of them are based on features describing the serial dependence patterns between each pair of categories. The first dissimilarity ...
