Proceedings of the 2016 5th International Conference on Advanced Materials and Computer Science

Prediction of transmission counts by a radial basis function neural network

Authors
Ke Cao, Qi Shen, Jie Liao Meng
Corresponding Author
Ke Cao
Available Online June 2016.
DOI
10.2991/icamcs-16.2016.91How to use a DOI?
Keywords
rbf neural network, Fruit fly Optimization Algorithm, blogs’ rewet counts.
Abstract

The microblog as a platform used to serve the communication of the internet, has been developing rapidly. The blog has become an important way to get information and to transmit information [1]. The blog message can be transmitted, and we as consumer can transmit them by a few simple and convenient operation. As to the suddenly happened situation, the transmission can cause a very direct influence to the transmission and spread of the situation itself. Here we set an example of the topic, the share of the photography course, and we also refer rbf neural network to the research of the transmission of the relevant situations, and we will continue the optimization of width status in the kernel function combining Fruit fly Optimization Algorithm. First, this essay analyzes different factors effecting blog’s rewet counts in many different aspects. On this base, we classify the blogs according to the rewet counts, and we predict the blogs’ rewet counts by rbf basing on the foa, which has been optimized. Under different numbers’ samples, the experimental result has certain reference value by contrasting and analyzing the predicted result of foa-rbf model.

Copyright
© 2016, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Volume Title
Proceedings of the 2016 5th International Conference on Advanced Materials and Computer Science
Series
Advances in Engineering Research
Publication Date
June 2016
ISBN
10.2991/icamcs-16.2016.91
ISSN
2352-5401
DOI
10.2991/icamcs-16.2016.91How to use a DOI?
Copyright
© 2016, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - Ke Cao
AU  - Qi Shen
AU  - Jie Liao Meng
PY  - 2016/06
DA  - 2016/06
TI  - Prediction of transmission counts by a radial basis function neural network
BT  - Proceedings of the 2016 5th International Conference on Advanced Materials and Computer Science
PB  - Atlantis Press
SP  - 433
EP  - 437
SN  - 2352-5401
UR  - https://doi.org/10.2991/icamcs-16.2016.91
DO  - 10.2991/icamcs-16.2016.91
ID  - Cao2016/06
ER  -