Πλοήγηση ανά Θέμα "Clustering algorithms"
Αποτελέσματα 21-40 από 41
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Feature Selection in Single-Cell RNA-seq Data via a Genetic Algorithm
(2021)Big data methods prevail in the biomedical domain leading to effective and scalable data-driven approaches. Biomedical data are known for their ultra-high dimensionality, especially the ones coming from molecular biology ... -
A hybrid metaheuristics-based algorithm for electricity load curves profiling
(2021)Clustering-based load profiling utilizes unsupervised machine learning algorithms to form homogenous clusters composed by electricity load curves with similar characteristics. Due to the importance of load profiling in ... -
Investigating the efficiency of machine learning algorithms on mapreduce clusters with SSDs
(2018)In the big data era, the efficient processing of large volumes of data has became a standard requirement for both organizations and enterprises. Since single workstations cannot sustain such tremendous workloads, MapReduce ... -
Load curves partitioning with the application of soft clustering algorithms
(2019)Load profiling refers to a procedure which leads to the formulation of daily load curve and consumer categories regarding the similarity of their curves shapes. This procedure incorporates a set of pattern recognition ... -
A machine learning pipeline for predicting joint space narrowing in knee osteoarthritis patients
(2020)Osteoarthritis is the common form of arthritis in the knee (KOA). It is identified as one of the main causes of pain leading even to disability. To exploit the continuous increase in medical data concerning KOA, various ... -
Minimum weighted clustering algorithm for wireless sensor networks
(2015)Extending network lifetime is a primary design objective for a wireless sensor network (WSN). Efficient clustering among sensor nodes seems a promising solution to evenly balance energy consumption and thus extend node and ... -
Multi-optima search using Differential Evolution and unsupervised clustering
(2013)The aim of this paper is the combination of an Evolutionary Algorithm and a Data Mining technique for the location and computation of multiple local and global optima of an objective function. To accomplish this task we ... -
Node clustering in wireless sensor networks by considering structural characteristics of the network graph
(2007)The deployment of wireless sensor networks in many application areas, e.g., aggregation services, requires self-organization of the network nodes into clusters. Quite a lot of node clustering techniques have appeared in ... -
Nonlinear dimensionality reduction for clustering
(2020)We introduce an approach to divisive hierarchical clustering that is capable of identifying clusters in nonlinear manifolds. This approach uses the isometric mapping (Isomap) to recursively embed (subsets of) the data in ... -
Predictive intelligence to the edge through approximate collaborative context reasoning
(2018)We focus on Internet of Things (IoT) environments where a network of sensing and computing devices are responsible to locally process contextual data, reason and collaboratively infer the appearance of a specific phenomenon ... -
Projection based clustering of gene expression data
(2010)The microarray DNA technologies have given researchers the ability to examine, discover and monitor thousands of genes in a single experiment. Nonetheless, the tremendous amount of data that can be obtained from microarray ... -
A prosumer model based on smart home energy management and forecasting techniques
(2021)This work presents an optimization framework based on mixed-integer programming techniques for a smart home’s optimal energy management. In particular, through a cost-minimization objective function, the developed approach ... -
Reference table based k-anonymous private blocking
(2012)Privacy Preserving Record Linkage is an emerging field of research which attempts to deal with the classical linkage problem from a privacy preserving point of view. In this paper we propose a novel approach for performing ... -
Remotely sensed data fusion for spatiotemporal geostatistical analysis of forest fire hazard
(2020)Forest fires are a natural phenomenon which might have severe implications on natural and anthropogenic ecosystems. Future projections predict that, under a climate change environment, the fire season would be lengthier ... -
RLAC: Random Line Approximation Clustering
(2021)We explore how Random Projections can be used as an Approximate method for Projection Pursuit Clustering in high dimensional data. Traditional data transformations such as PCA for dimensionality reduction have been shown ... -
A Scalable Short-Text Clustering Algorithm Using Apache Spark
(2021)Short text clustering deals with the problem of grouping together semantically similar documents with small lengths. Nowadays, huge amounts of text data is being generated by numerous applications such as microblogs, ... -
Skin lesions characterisation utilising clustering algorithms
(2010)In this paper we propose a clustering technique for the recognition of pigmented skin lesions in dermatological images. It is known that computer vision-based diagnosis systems have been used aiming mostly at the early ... -
Social clustering of vehicles based on semi-Markov processes
(2016)Vehicle clustering is a crucial network management task for vehicular networks to address the broadcast storm problem and to cope with the rapidly changing network topology. Developing algorithms that create stable clusters ... -
Supervised papers classification on large-scale high-dimensional data with apache spark
(2018)The problem of classifying a research article into one or more fields of science is of particular importance for the academic search engines and digital libraries. A robust classification algorithm offers the users a wide ... -
Unsupervised clustering and multi-optima evolutionary search
(2014)This paper pursues a course of investigation of an approach to combine Evolutionary Computation and Data Mining for the location and computation of multiple local and global optima of an objective function. To accomplish ...