Paper Title:
Cusp Catastrophe Intelligence Combinatorial Prediction of Land Subsidence
| Periodical | Applied Mechanics and Materials (Volumes 155 - 156) |
|---|---|
| Main Theme | Mechanical Engineering and Green Manufacturing II |
| Edited by | Shaobo Zhong and Xilong Qu |
| Pages | 606-610 |
| DOI | 10.4028/www.scientific.net/AMM.155-156.606 |
| Citation | Chong Hao Huang et al., 2012, Applied Mechanics and Materials, 155-156, 606 |
| Online since | February, 2012 |
| Authors | Chong Hao Huang, Yu Song Lu, Guo Bao, Zhen Rong Lin |
| Keywords | Cusp Catastrophe, Grey-Neural Network, Predict Precision, Prediction of Land Subsidence, Weighted Coefficient |
| Price | US$ 28,- |
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Abstract
Seeking for a scientific and reasonable predict model is the key point to ensure accurate and reliable prediction results for the land subsidence. In this paper, the research of subsidence area pointed out by picks the process of land subsidence which causes by the water reservoir that conforms to the characteristic of nonlinear dynamics, thus, a new model is established to solve the combinatorial weighted coefficients by using the predict precision, and a simple method is introduced to solve the grey model and neural network combination forecast model. Based on many examples, the new cusp catastrophe land subsidence model is proved to be very effective and much more accurate.
