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Fuzzy based clustering in CWPSN using machine learning model

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Title Fuzzy based clustering in CWPSN using machine learning model
 
Creator M, Bhuvaneswari
S, Sasi Priya
R, Arun Chakravarthy
 
Subject Energy harvesting
Greedy algorithm
CNN
Primary user
Machine learning
Artificial intelligence
 
Description 90-94
Cognitive wireless power sensor network (CWPSN) technology, widely used in almost all fields, has addressed various issues. The
researchers have addressed the problems in the lack of radio spectrum availability and enabled the allocation of dynamic spectrum
access in specific fields. The main challenge has been to support the radio spectrum allocation using intelligent adaptive learning
and decision-making techniques so that various requirements of 5G wireless networks can be encountered. Machine learning (ML)
is one of the most promising artificial intelligence tools conceived to support cognitive wireless networks. This paper aims to
provide energy optimization and enhance security to cognitive wireless power sensor networks using a novel protocol during
resource allocation. In addition to the existing methods, a novel protocol, fuzzy cluster-based greedy algorithms for attack
prediction and energy harvesting using a machine-language model based on neural network techniques have been introduced. The
simulation has been done using MATLAB software tools which gives efficient results.
 
Date 2021-12-28T09:33:46Z
2021-12-28T09:33:46Z
2021-06
 
Type Article
 
Identifier 0975-105X (Online); 0367-8393 (Print)
http://nopr.niscair.res.in/handle/123456789/58755
 
Language en
 
Publisher NIScPR-CSIR, India
 
Source IJRSP Vol.50(2) [June 2021]