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In order to solve the problem of instability clustering in Ad Hoc Networks with complex and changeable node motion, this paper proposes a weighted clustering algorithm based on node stability(SA-WCA). In this algorithm, we propose a node stability factor based on node received power, which does not need to calculate the specific distance between nodes and can only judge the relative motion between...
This paper presents the development of an algorithm based on K-Means clustering and probabilistic neural network (PNN) for classifying the industrial system faults. The proposed technique consists of a preprocessing unit based on K-Means clustering and probabilistic neural network (PNN). Given a set of data points, firstly the K-Means algorithm is used to obtain K-temporary clusters, and then PNN...
In clustering methods, the estimation of the optimal number of clusters is significant for subsequent analysis. As a simple clustering method, the fuzzy c-means algorithm (FCM) has been widely discussed and applied in pattern recognition and machine learning. However, the FCM could not guarantee unique clustering result because initial cluster number is chosen randomly. As the number of clusters is...
Localization of sensor nodes is a challenging and crucial issue in wireless sensor networks (WSNs), and high precision and low cost algorithms become the research direction. In this paper, a robust and accurate localization algorithm based on adjustment of trilateration network (LATN) for WSNs is presented. Firstly, uncomplicated distributed algorithm is used for estimating position of the nodes,...
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