TY - CHAP
T1 - Reduced rule-base fuzzy-neural networks
AU - Terziyska, Margarita
AU - Todorov, Yancho
PY - 2017/1/1
Y1 - 2017/1/1
N2 - In this paper two different fuzzy-neural systems with reduced fuzzy rules bases, namely Distributed Adaptive Neuro Fuzzy Architecture (DANFA) and Semi Fuzzy Neural Network (SFNN), are presented. Both structures are realized with Takagi-Sugeno fuzzy inference mechanism and they posses reduced number of parameters for update during the learning procedure. Thus, the computational time for algorithm execution is additionally reduced, which make the modeling structures a promising solution for real time applications. As a learning approach for the designed structures a simplified two-step gradient descent approach is implemented. To demonstrate the potentials of both models, simulation experiments with two benchmark chaotic time systems—Mackey-Glass and Rossler are studied. The obtained results show accurate models performance with minimal prediction error.
AB - In this paper two different fuzzy-neural systems with reduced fuzzy rules bases, namely Distributed Adaptive Neuro Fuzzy Architecture (DANFA) and Semi Fuzzy Neural Network (SFNN), are presented. Both structures are realized with Takagi-Sugeno fuzzy inference mechanism and they posses reduced number of parameters for update during the learning procedure. Thus, the computational time for algorithm execution is additionally reduced, which make the modeling structures a promising solution for real time applications. As a learning approach for the designed structures a simplified two-step gradient descent approach is implemented. To demonstrate the potentials of both models, simulation experiments with two benchmark chaotic time systems—Mackey-Glass and Rossler are studied. The obtained results show accurate models performance with minimal prediction error.
UR - http://www.scopus.com/inward/record.url?scp=85012247629&partnerID=8YFLogxK
U2 - 10.1007/978-3-319-49544-6_17
DO - 10.1007/978-3-319-49544-6_17
M3 - Chapter or book article
AN - SCOPUS:85012247629
SN - 978-3-31949543-9
T3 - Studies in Computational Intelligence
SP - 199
EP - 214
BT - Advanced Computing in Industrial Mathematics - Revised Selected Papers of the 10th Annual Meeting of the Bulgarian Section of SIAM
A2 - Georgiev, Ivan
A2 - Todorov, Michail
A2 - Georgiev, Krassimir
PB - Springer
T2 - 10th Annual Meeting of the Bulgarian Section of SIAM, BGSIAM 2015
Y2 - 21 December 2015 through 22 December 2015
ER -