Optimization of RBF Neural Networks Using a Rough K-Means Algorithm and Application to Naphtha Dry Point Soft Sensors
スポンサーリンク
概要
- 論文の詳細を見る
Since the optimal construction of a Radial Basis Function Neural Network (RBF-NN) is difficult to determine and plays an important role in predicting performance, we propose a modified RBF-NN, which is integrated with the K-Means clustering based on the Rough sets theory (Rough K-Means), in order to optimize the number of hidden neurons. First, an original RBF-NN that superposes each center to a training set point is built and the network is trained to obtain the potential relationships between the input and output variables. Next, Rough K-Means is employed to optimize the structure and weights of the RBF-NN by clustering the output from the hidden layer that is due to the cluster uncertainty of the hidden output. Further, RBF-NN with Rough K-Means and K-Means, respectively, are employed to develop naphtha dry point soft sensors. The results show that the Rough K-Means is more effective in handling uncertainty and that RBF-NN with Rough K-Means is superior to RBF-NN with K-Means.
著者
-
Chen Chao
Key Laboratory For Neuroinformation Of Ministry Of Education School Of Life Science And Technology U
-
Zhou Weihua
Key Laboratory of Advanced Control and Optimization for Chemical Processes of Ministry of Education, East China University of Science and Technology
-
Yan Xuefeng
Key Laboratory of Advanced Control and Optimization for Chemical Processes of Ministry of Education, East China University of Science and Technology
-
Chen Chao
Key Laboratory of Advanced Control and Optimization for Chemical Processes of Ministry of Education, East China University of Science and Technology
-
Guo Meijin
State Key Laboratory of Bioreactor Engineering, East China University of Science and Technology
関連論文
- Molecular cloning, characterization and tissue distribution of six splice variants of activin type IIA receptor (ActRIIA) from grass carp (Ctenopharyngodon idellus)
- Comparison of the Effects of Short-Term UVB Radiation Exposure on Phytoplankton Photosynthesis in the Temperate Changjiang and Subtropical Zhujiang Estuaries of China
- Optimization of RBF Neural Networks Using a Rough K-Means Algorithm and Application to Naphtha Dry Point Soft Sensors