Search results for "Clustering algorithm"
showing 10 items of 34 documents
Clustering ball possession duration according to players’ role in football small-sided games
2022
This study aimed to explore which offensive variables best discriminate the ball possession duration according to players specific role (defenders, midfielders, attackers) during a Gk+3vs3+Gk football small-sided games. Fifteen under-15 players (age 13.2±1.0 years, playing experience 4.2±1.0 years) were grouped according to their positions (team of defenders, n = 5; team of midfielders, n = 7; team of attackers, n = 3). On each testing day (n = 3), each team performed one bout of 5-min against each team in a random order, accounting for a total of nine bouts in the following scenarios: i) defenders vs midfielders; ii) defenders vs attackers; iii) midfielders vs attackers. Based on video, a …
A hybrid algorithm for planning public charging stations
2014
International audience; Green mobility solutions are receiving currently an enormous attention. Indeed, during last years, electric vehicles, being part of the field of the smart-grid, entered the automobile market of the whole world. This technology requires an effective deployment of charging stations of electric refill since the main problem in this system remains over the duration of refill of the batteries. In this work, we propose an optimized algorithm to locate electric charging stations. The main task of the algorithm is to find the best site of charging stations locations so as to minimize loss on the way to the charging station, as well as minimize investment cost, we take into a…
Multi-party metering: An architecture for privacy-preserving profiling schemes
2013
Several privacy concerns about the massive deploy- ment of smart meters have been arisen recently. Namely, it has been shown that the fine-grained temporal traces generated by these meters can be correlated with different users behaviors. A new architecture, called multi-party metering, for enabling privacy-preserving analysis of high-frequency metering data without requiring additional complexity at the smart meter side is here proposed. The idea is to allow multiple entities to get a share of the high-frequency metering data rather than the real data, where this share does not reveal any information about the real data. By aggregating the shares provided by different users and publishing …
Quantifying unpredictability: A multiple-model approach based on satellite imagery data from Mediterranean ponds.
2017
Fluctuations in environmental parameters are increasingly being recognized as essential features of any habitat. The quantification of whether environmental fluctuations are prevalently predictable or unpredictable is remarkably relevant to understanding the evolutionary responses of organisms. However, when characterizing the relevant features of natural habitats, ecologists typically face two problems: (1) gathering long-term data and (2) handling the hard-won data. This paper takes advantage of the free access to long-term recordings of remote sensing data (27 years, Landsat TM/ETM+) to assess a set of environmental models for estimating environmental predictability. The case study inclu…
Solution Using Clustering Methods
1987
The main aim of this analysis is to find out typical morphologies from the multivariate and longitudinal data set on growing children and to describe the morphological evolution of the found groups of girls. The finding out of typical morphologies is, in our opinion, strictly linked to the search of structures in the individuals and in the variables.
Use of Time-Frequency map combined with DBSCAN algorithm for separation of partial discharge pulses under DC voltage
2022
The Phase-Resolved-Partial-Discharge pattern (PRPD) is a conventional technique used for the evaluation of partial discharges (PD) phenomena in High-Voltage-Alternating-Current (HVAC) systems. This map is constructed by plotting the peak of each detected pulses as a function of the phase angle of the supply voltage. Therefore it is obvious that this technique cannot be used for the analysis of data from PD mesaurement under different supply voltage condition (DC). The aim of this paper is to evaluate the application of the Time-Frequency map (TF map) for the analysis of a dataset obtained from PD measurement under DC voltage. A density-based clustering algorithm was also used to gain more i…
Robust Synchronization-Based Graph Clustering
2013
Complex graph data now arises in various fields like social networks, protein-protein interaction networks, ecosystems, etc. To reveal the underlying patterns in graphs, an important task is to partition them into several meaningful clusters. The question is: how can we find the natural partitions of a complex graph which truly reflect the intrinsic patterns? In this paper, we propose RSGC, a novel approach to graph clustering. The key philosophy of RSGC is to consider graph clustering as a dynamic process towards synchronization. For each vertex, it is viewed as an oscillator and interacts with other vertices according to the graph connection information. During the process towards synchro…
An algorithm for earthquakes clustering based on maximum likelihood
2007
In this paper we propose a clustering technique set up to separate and find out the two main components of seismicity: the background seismicity and the triggered one. We suppose that a seismic catalogue is the realization of a non homogeneous space-time Poisson clustered process, with a different parametrization for the intensity function of the Poisson-type component and of the clustered (triggered) component. The method here proposed assigns each earthquake to the cluster of earthquakes, or to the set of independent events, according to the increment to the likelihood function, computed using the conditional intensity function estimated by maximum likelihood methods and iteratively chang…
CLUSTERING INCOMPLETE SPECTRAL DATA WITH ROBUST METHODS
2018
Abstract. Missing value imputation is a common approach for preprocessing incomplete data sets. In case of data clustering, imputation methods may cause unexpected bias because they may change the underlying structure of the data. In order to avoid prior imputation of missing values the computational operations must be projected on the available data values. In this paper, we apply a robust nan-K-spatmed algorithm to the clustering problem on hyperspectral image data. Robust statistics, such as multivariate medians, are more insensitive to outliers than classical statistics relying on the Gaussian assumptions. They are, however, computationally more intractable due to the lack of closed-for…
SparseHC: A Memory-efficient Online Hierarchical Clustering Algorithm
2014
Computing a hierarchical clustering of objects from a pairwise distance matrix is an important algorithmic kernel in computational science. Since the storage of this matrix requires quadratic space with respect to the number of objects, the design of memory-efficient approaches is of high importance to this research area. In this paper, we address this problem by presenting a memory-efficient online hierarchical clustering algorithm called SparseHC. SparseHC scans a sorted and possibly sparse distance matrix chunk-by-chunk. Meanwhile, a dendrogram is built by merging cluster pairs as and when the distance between them is determined to be the smallest among all remaining cluster pairs. The k…