نتایج جستجو برای: test for clustering
تعداد نتایج: 10566381 فیلتر نتایج به سال:
We quantitatively compare a particle implementation of the adhesion approximation to fully non–linear, numerical “N–body” simulations. Our primary tool, cross–correlation of N–body simulations with the adhesion approximation, indicates good agreement, better than that found by the same test performed with the Zel’dovich approximation (hereafter ZA). However, the cross–correlation is not as good...
Assigning a set of objects to groups such that objects in one group or cluster are more similar to each other than the other clusters’ objects is the main task of clustering analysis. SSPCO optimization algorithm is anew optimization algorithm that is inspired by the behavior of a type of bird called see-see partridge. One of the things that smart algorithms are applied to solve is the problem ...
having conducted the experiment and analysed the data, the researcher computed the groups mean scores and variances for the test relating to the research question. as the final atep, a t-test was conodonted for the hypothesis. as noted earlier, the significance level was determined at .05 and .01 respectively. the observed t-value was higher than the critical t-value at. 5 and .01 levels. conse...
بررسی رابطه بین یادگیری سازمانی و توانمندسازی مدیران و معاونین مدارس شهرستان میانه دکتر محمد اورکی1، دکتر هاشم نعمتی، گلسیما عزیزی* استادیار گروه علوم تربیتی ، دانشگاه پیام نور تهران جنوب استادیار گروه علوم تربیتی. ، دانشگاه پیام نور مشهد دانشجوی کارشناسی ارشد مدیریت آموزشی ، دانشگاه پیام نور تهران جنوب [email protected] میانه- دانشگاه پیام نور میانه مدیر آموزشی، 2226062 – 0423، ت...
The detection and prevention of crime, in the past few decades, required several years of research and analysis. However, today, thanks to smart systems based on data mining techniques, it is possible to detect and prevent crime in a considerably less time. Classification and clustering-based smart techniques can classify and cluster the crime-related samples. The most important factor in the c...
Clustering is the process of division of a dataset into subsets that are called clusters, so that objects within a cluster are similar to each other and different from objects of the other clusters. So far, a lot of algorithms in different approaches have been created for the clustering. An effective choice (can combine) two or more of these algorithms for solving the clustering problem. Ensemb...
One of the main issues in fuzzy clustering is to determine the number of clusters that should be available before clustering and selection of different values for the number of clusters will lead to different results. Then, different clusters obtained from different number of clusters should be validated with an index. But so far such an index has not been introduced for interval type-2 fuzzy C...
In this study, a novel path clustering technique for adaptive path delay testing, where the test paths are altered according to the extracted device parameters, is proposed. The proposed algorithm is based on the k-means++ algorithm. By considering the probability function of the die-to-die systematic process variation, the proposed algorithm clusters path sets to minimize the total number of t...
energy consumption is considered as a critical issue in wireless sensor networks (wsns). batteries of sensor nodes have limited power supply which in turn limits services and applications that can be supported by them. an efcient solution to improve energy consumption and even trafc in wsns is data aggregation (da) that can reduce the number of transmissions. two main challenges for da are: (i)...
Choosing test cases for the optimization process of information systems testing is crucial, because it helps to eliminate unnecessary and redundant testing data. However, its use in systems that address complex domains (e.g. images) is still underexplored. This paper presents a new approach that uses Content-Based Image Retrieval (CBIR), similarity functions and clustering techniques to select ...
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