نتایج جستجو برای: means clustering method

تعداد نتایج: 1976222  

In recent years, the advancement of information gathering technologies such as GPS and GSM networks have led to huge complex datasets such as time series and trajectories. As a result it is essential to use appropriate methods to analyze the produced large raw datasets. Extracting useful information from large data sets has always been one of the most important challenges in different sciences,...

پایان نامه :وزارت علوم، تحقیقات و فناوری - دانشگاه پیام نور - دانشگاه پیام نور استان همدان - دانشکده ادبیات و علوم انسانی 1390

abstract this study is an attempt to determine the effect of nano- technology education on science lesson for fifth grade in primary school in the city of kermanshah. this research is experimental and is conducted in the from of pre-test and post- test for the control group. an achievement test was administered to determine the rate of learning in the students. the research is an applied one. ...

Journal: :journal of tethys 0

a well-known algorithm of clustering is k-means by which the data are divided into k classes based upon a distance criterion. in the present research, by using k-means method for classifying data derived from exploration boreholes in the parkam deposit, the optimum k has been calculated and then the data have been clustered and the relative geochemical behavioral characteristics analyzed. the c...

2007
MICHAEL DENNING JOEL KASTNER CHESTER F. CARLSON

.......................................................................................................2 Background .................................................................................................5 Stars and Spectroscopy with the Spitzer Space Telescope .................................5 Clustering Methodologies .....................................................................

Clustering algorithms are highly dependent on different factors such as the number of clusters, the specific clustering algorithm, and the used distance measure. Inspired from ensemble classification, one approach to reduce the effect of these factors on the final clustering is ensemble clustering. Since weighting the base classifiers has been a successful idea in ensemble classification, in th...

2009
Carole Frindel Marc C. Robini Joël Schaerer Pierre Croisille Yue Min Zhu

Cardiac fibre architecture plays a key role in heart function. Recently, the estimation of fibre structure has been simplified with diffusion tensor MRI (DT-MRI). In order to assess the heart architecture and its underlying function, with the goal of dealing with pathological tissues and easing inter-patient comparisons, we propose a methodology for finding cardiac myofibrille trace corresponde...

Journal: :international journal of supply and operations management 0
mohammad mirabi department of industrial engineering, ayatollah haeri university of meybod, meybod, yazd, iran nasibeh shokri group of industrial engineering, elm-o-honar university, yazd iran ahmad sadeghieh group of industrial engineering, yazd university, yazd, iran

this paper considers the multi-depot vehicle routing problem with time window in which each vehicle starts from a depot and there is no need to return to its primary depot after serving customers. the mathematical model which is developed by new approach aims to minimizing the transportation cost including the travelled distance, the latest and the earliest arrival time penalties. furthermore, ...

Journal: :journal of computer and robotics 0
sahifeh poor ramezani kalashami faculty of engineering, department of artificial intelligence, mashhad branch, islamic azad university, mashhad, iran seyyed javad seyyed mahdavi chabok faculty of engineering, department of artificial intelligence, mashhad branch, islamic azad university, mashhad, iran

clustering is one of the known techniques in the field of data mining where data with similar properties is within the set of categories. k-means algorithm is one the simplest clustering algorithms which have disadvantages sensitive to initial values of the clusters and converging to the local optimum. in recent years, several algorithms are provided based on evolutionary algorithms for cluster...

2017
Dino Oglic Thomas Gärtner

We investigate, theoretically and empirically, the effectiveness of kernel K-means++ samples as landmarks in the Nyström method for low-rank approximation of kernel matrices. Previous empirical studies (Zhang et al., 2008; Kumar et al., 2012) observe that the landmarks obtained using (kernel) K-means clustering define a good lowrank approximation of kernel matrices. However, the existing work d...

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