Male Rat's Liver Weight Molding Based on Grey Theory and RBF Neural Network

DOI

10.2991/amsm-16.2016.93How to use a DOI?

Keywords

liver weight of male rat; Grey theory; RBF neural network; MATLAB

Abstract

In order to research the relationship between male rat's liver weight and their body weight, Grey theory method and Radial Basis Function neural network method were used to model the liver related data in male rats. First of all, the sample standard deviations of the liver weight mean value were obtained by using Grey theory method. What's more, validated liver weight data in each group was in accord with normal distribution and calculated the upper and lower limits of liver weight distribution. The RBF neural network method was applied to fit the upper and lower limits of liver weight distribution and mean values in software R2011b MATLAB environment. Final fitting result which has practical value can be used to verify actual liver weight show relationship between liver weight and body weight, and then it can cut down test cost and cycle.

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  - Jianyang Lin
AU  - Jinjie Xu
AU  - Zhien Sun
PY  - 2016/05
DA  - 2016/05
TI  - Male Rat's Liver Weight Molding Based on Grey Theory and RBF Neural Network
BT  - Proceedings of the 2016 International Conference on Applied Mathematics, Simulation and Modelling
PB  - Atlantis Press
SP  - 414
EP  - 417
SN  - 2352-538X
UR  - https://doi.org/10.2991/amsm-16.2016.93
DO  - 10.2991/amsm-16.2016.93
ID  - Lin2016/05
ER  -