Cloud Neural Network Algorithm Based on Cloud Transformation
Liwei Han, Zongkun Li · 2008
For the aim of improving the simulation ability of neural network and being able to reflect the randomness, fuzziness and the relevance between the two existed in the real world, a new algorithm-cloud neural network(CNN) based on cloud transformation is presented in this paper. And the parameter adjustment method of CNN is given. The CNN based on cloud transformation could be used in the nonlinear system simulation successfully. Simulation example shows that CNN has a faster convergence rate and higher convergence accuracy in calculation. At the same time, the CNN also has better generalization ability, which means it has a broad prospect on application.