@article{(Open Science Index):https://publications.waset.org/pdf/6593,
	  title     = {Improving Convergence of Parameter Tuning Process of the Additive Fuzzy System by New Learning Strategy},
	  author    = {Thi Nguyen and  Lee Gordon-Brown and  Jim Peterson and  Peter Wheeler},
	  country	= {},
	  institution	= {},
	  abstract     = {An additive fuzzy system comprising m rules with
n inputs and p outputs in each rule has at least t m(2n + 2 p + 1)
parameters needing to be tuned. The system consists of a large
number of if-then fuzzy rules and takes a long time to tune its
parameters especially in the case of a large amount of training data
samples. In this paper, a new learning strategy is investigated to cope
with this obstacle. Parameters that tend toward constant values at the
learning process are initially fixed and they are not tuned till the end
of the learning time. Experiments based on applications of the
additive fuzzy system in function approximation demonstrate that the
proposed approach reduces the learning time and hence improves
convergence speed considerably.},
	    journal   = {International Journal of Computer and Information Engineering},
	  volume    = {2},
	  number    = {9},
	  year      = {2008},
	  pages     = {2929 - 2933},
	  ee        = {https://publications.waset.org/pdf/6593},
	  url   	= {https://publications.waset.org/vol/21},
	  bibsource = {https://publications.waset.org/},
	  issn  	= {eISSN: 1307-6892},
	  publisher = {World Academy of Science, Engineering and Technology},
	  index 	= {Open Science Index 21, 2008},
	}