Prediction of transmission counts by a radial basis function neural network

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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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  -