Name
Title | ||
|---|---|---|
Nonlinear System Identification by Gustafson–Kessel Fuzzy Clustering and Supervised Local Model Network Learning for the Drug Absorption Spectra Process |
Abstract | ||
|---|---|---|
This paper deals with the problem of fuzzy nonlinear model identification in the framework of a local model network (LMN). A new iterative identification approach is proposed, where supervised and unsupervised learning are combined to optimize the structure of the LMN. For the purpose of fitting the cluster-centers to the process nonlinearity, the Gustafsson-Kessel (GK) fuzzy clustering, i.e., unsupervised learning, is applied. In combination with the LMN learning procedure, a new incremental method to define the number and the initial locations of the cluster centers for the GK clustering algorithm is proposed. Each data cluster corresponds to a local region of the process and is modeled with a local linear model. Since the validity functions are calculated from the fuzzy covariance matrices of the clusters, they are highly adaptable and thus the process can be described with a very sparse amount of local models, i.e., with a parsimonious LMN model. The proposed method for constructing the LMN is finally tested on a drug absorption spectral process and compared to two other methods, namely, Lolimot and Hilomot. The comparison between the experimental results when using each method shows the usefulness of the proposed identification algorithm. |
Year | DOI | Venue |
|---|---|---|
2011 | 10.1109/TNN.2011.2170093 | IEEE Transactions on Neural Networks |
Keywords | Field | DocType |
adsorption,covariance matrices,drugs,fuzzy set theory,iterative methods,medical computing,pattern clustering,unsupervised learning,Gustafson-Kessel fuzzy clustering,data cluster,drug absorption spectra process,drug absorption spectral process,fuzzy covariance matrix,fuzzy nonlinear model identification,incremental method,iterative identification approach,nonlinear system identification,process nonlinearity,supervised local model network learning,unsupervised learning,(un)supervised learning,Gustafson–Kessel fuzzy clustering,local model networks,nonlinear system identification | Fuzzy clustering,Pattern recognition,Iterative method,Computer science,Fuzzy logic,Nonlinear system identification,Fuzzy set,Unsupervised learning,Artificial intelligence,Artificial neural network,Cluster analysis,Machine learning | Journal |
Volume | Issue | ISSN |
22 | 12 | 1045-9227 |
Citations | PageRank | References |
14 | 0.71 | 23 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Luka Teslić | 1 | 24 | 1.29 |
| Benjamin Hartmann | 2 | 23 | 1.77 |
| Oliver Nelles | 3 | 99 | 17.27 |
| Igor Skrjanc | 4 | 354 | 52.47 |