TY - JOUR
T1 - Self-boosting first-order autonomous learning neuro-fuzzy systems
AU - Gu, Xiaowei
AU - Angelov, Plamen Parvanov
N1 - Copyright:
Copyright 2019 Elsevier B.V., All rights reserved.
PY - 2019/4/1
Y1 - 2019/4/1
N2 - In this paper, a detailed mathematical analysis of the optimality of the premise and consequent parts of the recently introduced first-order Autonomous Learning Multi-Model (ALMMo) neuro-fuzzy system is conducted. A novel self-boosting algorithm for structure- and parameter-optimization is, then, introduced to the ALMMo, which results in the self-boosting ALMMo (SBALMMo) neuro-fuzzy system. By minimizing the objective functions with the previously collected data, the SBALMMo is able to optimize its system structure and parameters in few iterations. Numerical examples based benchmark datasets and real-world problems demonstrate the effectiveness and validity of the SBALMMo, and show the strong potential of the proposed approach for real applications.
AB - In this paper, a detailed mathematical analysis of the optimality of the premise and consequent parts of the recently introduced first-order Autonomous Learning Multi-Model (ALMMo) neuro-fuzzy system is conducted. A novel self-boosting algorithm for structure- and parameter-optimization is, then, introduced to the ALMMo, which results in the self-boosting ALMMo (SBALMMo) neuro-fuzzy system. By minimizing the objective functions with the previously collected data, the SBALMMo is able to optimize its system structure and parameters in few iterations. Numerical examples based benchmark datasets and real-world problems demonstrate the effectiveness and validity of the SBALMMo, and show the strong potential of the proposed approach for real applications.
KW - Autonomous learning
KW - Local optimality
KW - Neuro-fuzzy systems
KW - Self-boosting
KW - Streaming data processing
UR - http://www.research.lancs.ac.uk/portal/en/publications/selfboosting-firstorder-autonomous-learning-neurofuzzy-systems(fbb5cf8c-5dd0-48aa-baac-170ebdeaf341).html
UR - http://www.scopus.com/inward/record.url?scp=85060475708&partnerID=8YFLogxK
U2 - 10.1016/j.asoc.2019.01.005
DO - 10.1016/j.asoc.2019.01.005
M3 - Article
SN - 1568-4946
VL - 77
SP - 118
EP - 134
JO - Applied Soft Computing
JF - Applied Soft Computing
ER -