Name
Abstract | ||
|---|---|---|
In this paper various types of classifiers for quantitatively identify teletraffic service devices are proposed. The classification method “K - Nearest Neighbors With Defined Cityblock Metric Distance At Three Nearest Neighbors” is selected. A classifier structure is synthesized based on Adaptive Neuro-Fuzzy Interface Systems (ANFIS) in hybrid learning algorithm and Gaussian type membership function of the input variables. Results are obtained for variation of mean square error and classification accuracy in a variation of neurons in the hidden layers of artificial neural networks with different number of output neurons and method of encoding target classes. A network structure with better performance is selected based on the parameters values of linear regression and correlation. |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1109/BlackSeaCom.2016.7901585 | 2016 IEEE International Black Sea Conference on Communications and Networking (BlackSeaCom) |
Keywords | Field | DocType |
Communication and Information Theory,ANN,ANFIS and K-NN Classificators | Pattern recognition,Computer science,Mean squared error,Metric (mathematics),Gaussian,Artificial intelligence,Adaptive neuro fuzzy inference system,Classifier (linguistics),Statistical classification,Artificial neural network,Membership function | Conference |
ISBN | Citations | PageRank |
978-1-5090-1926-7 | 0 | 0.34 |
References | Authors | |
3 | 5 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ivelina Balabanova | 1 | 0 | 0.34 |
| Georgi Georgiev | 2 | 113 | 26.61 |
| Pencho Penchev | 3 | 0 | 0.34 |
| Stela Kostadinova | 4 | 0 | 0.34 |
| Rozalina Dimova | 5 | 6 | 1.22 |