BP Neural Network Based Animation Production Prediction

Author:

Tao Ran1,Yuan Da Chao1,Hu Gang Yi2

Affiliation:

1. Wuhan University of Technology

2. Southwest Forestry University

Abstract

In order to research the basic condition of animation production, this article chooses BP Neural Network to predict the animation production. We select 13 test samples, selected nine of them randomly as training samples, and the remaining four as the test samples. The coefficient of determination is 0.99839 and the mean relative error is 0.186125. The result shows that BP Neural Network is an effective prediction method.

Publisher

Trans Tech Publications, Ltd.

Reference6 articles.

1. Zhuandong Wang, Lin Zheng: Animation industry analysis and derivative product development. Tsinghua University Press, 2009 (in Chinese).

2. Jikai Yi, Yuanbing Hou: Intelligent control technology. Beijing University Press, 1999. (in Chinese).

3. Yaonan Wang: Intelligent control system. Hunan University Press, 2006. (in Chinese).

4. YueFeng Sun, HaoTian Chang, Zheng Jian Miao: Research on BP Neural Network Model for Water Demand Forecasting and its Application, Applied Mechanics and Materials, 2012. 170-173, 2352-2355.

5. WeiCui, XianDe Zhuo, WeiHua,: The Research on the BP-Neural-Network-Based Pre-Warning System for the Sustainable Forestry Economic Development, Applied Mechanics and Materials , 2013. 373-375, 1164-1167.

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