Distributed soft clustering method in Internet-of-Things environment based on average consensus algorithm

Abstract

The invention relates to a distributed soft clustering method in an Internet-of-Things environment based on an average consensus algorithm, and the method comprises the following specific steps: S1, obtaining a topological network where a target Internet-of-Things node is located, and inputting a distributed data set, a clustering number, a fuzzy coefficient and a stop criterion parameter into thetopological network; S2, initializing set elements of the distributed data set, and calculating the initial clustering center of the target Internet-of-Things node; S3, calculating a distribution matrix from the distributed data set to the initial clustering center; S4, calculating a clustering center in the target Internet-of-Things according to the distribution matrix, and obtaining a global clustering center through an average consensus algorithm; and S5, repeating the steps S1-S4, iteratively updating the global clustering center, judging the current global clustering center and the global clustering center of the previous round according to the stop criterion parameters, and outputting a final global clustering center. Compared with the prior art, the method has the advantages that the clustering result quality and the algorithm stability can be effectively improved, and the like.

Description

technical field [0001] The invention relates to the field of machine learning, in particular to a distributed soft clustering method based on an average consensus algorithm under the Internet of Things environment. Background technique [0002] An extension of the Internet, the Internet of Things (IoT), which connects machines and devices with services, is one of the most promising areas of technology today. Due to the surge in data volume in the Internet of Things and the security considerations of IoT devices, traditional centralized storage and computing platforms are facing challenges. In many application scenarios such as medical health, social media, etc., there is a need to obtain hidden information and structures of data, and these data are scattered in distributed IoT nodes, which increases the difficulty of data acquisition. In the algorithm model of data analysis and mining, clustering algorithm is a kind of simple and effective algorithm, and soft clustering alg...

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Problems solved by technology

[0004] The purpose of the present invention is to provide a distributed soft clustering method based on the average consensus algorithm in the Internet of Things environment in order to overcome the defects that the soft clustering algorithm in the prior art is greatly affected by the data set and has low stability.

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