Times Series Forecasting using Chebyshev Functions based Locally Recurrent neuro-Fuzzy Information System
The model proposed in this paper, is a hybridization of fuzzy neural network (FNN) and a functional link neural system for time series data prediction. The TSK-type feedforward fuzzy neural network does not take the full advantage of the use of the fuzzy rule base in accurate input-output mapping an...
Main Authors: | A.K. Parida, R. Bisoi, P.K. Dash, S. Mishra |
---|---|
Format: | Article |
Language: | English |
Published: |
Atlantis Press
2017-01-01
|
Series: | International Journal of Computational Intelligence Systems |
Subjects: | |
Online Access: | https://www.atlantis-press.com/article/25865513/view |
Similar Items
-
Chebyshev polynomial functions based locally recurrent neuro-fuzzy information system for prediction of financial and energy market data
by: A.K. Parida, et al.
Published: (2016-09-01) -
Orthogonality Properties of the Pseudo-Chebyshev Functions (Variations on a Chebyshev’s Theme)
by: Clemente Cesarano, et al.
Published: (2019-02-01) -
The Use of Chebyshev Polynomials in Numerical Analysis
by: Forisha, Donnie R.
Published: (1975) -
Direct Chebyshev approximation
by: Henderson, John Robert
Published: (2011) -
The Third and Fourth Kind Pseudo-Chebyshev Polynomials of Half-Integer Degree
by: Clemente Cesarano, et al.
Published: (2019-02-01)