International Journal of Advance Computational Engineering and Networking (IJACEN)
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Statistics report
Sep. 2020
Submitted Papers : 80
Accepted Papers : 10
Rejected Papers : 70
Acc. Perc : 12%
Issue Published : 90
Paper Published : 1248
No. of Authors : 3136
  Journal Paper

Paper Title
A Scheme of Anomalous Detection based on Deep Learning for Load Balancing in Wireless Networks

Abstract
There are used to define patterns of malicious network loads, while anomalous detections is more suitable for detecting normal and anomalous network loads in wireless networks. The important goal of these issues is to recognize the anomalous detections for better preparation against future load balancing of wireless networks. The deep learning based object recognition approaches attracting more attention to the researcher due to the revolution of a neural network parts called deep learning. Therefore, we propose an agent Detectbot that processes anomalous detection for load balancing based on deep learning in this paper. Keywords - Deep Learning, Load Balancing, Anomalous Detection, Wireless Networks


Author - Hye-Young Kim

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| Published on 2019-12-30
   
   
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