scholarly journals Parameter Estimation using Least Square Method for MIMO Takagi-Sugeno Neuro-Fuzzy in Time Series Forecasting

2008 ◽  
Vol 7 (2) ◽  
Author(s):  
Indar Sugiarto ◽  
Saravanakumar Natarajan
Keyword(s):  
Time Series ◽  
Parameter Estimation ◽  
Least Square Method ◽  
Time Series Forecasting ◽  
Least Square ◽  
Neuro Fuzzy ◽  
Takagi Sugeno

A hybrid neuro-fuzzy inference system-based algorithm for time series forecasting applied to energy consumption prediction

2020 ◽  
Vol 268 ◽  
pp. 114977 ◽  
Author(s):  
Mohammed Ali Jallal ◽  
Aurora González-Vidal ◽  
Antonio F. Skarmeta ◽  
Samira Chabaa ◽  
Abdelouhab Zeroual
Keyword(s):  
Time Series ◽  
Energy Consumption ◽  
Fuzzy Inference System ◽  
Fuzzy Inference ◽  
Time Series Forecasting ◽  
Inference System ◽  
Neuro Fuzzy ◽  
Energy Consumption Prediction ◽  
Consumption Prediction

scholarly journals Towards a Neuro-Fuzzy System for Time Series Forecasting in Maintenance Applications

2008 ◽  
Vol 41 (2) ◽  
pp. 12855-12860 ◽  
Author(s):  
M. El-Koujok ◽  
R. Gouriveau ◽  
N. Zerhouni
Keyword(s):  
Time Series ◽  
Fuzzy System ◽  
Time Series Forecasting ◽  
Neuro Fuzzy

United Estimation of Time Delay and Frequency Drift in XNAV

2014 ◽  
Vol 565 ◽  
pp. 187-193
Author(s):  
Zhen Ni He ◽  
Bao Jun Fei ◽  
Guo Zheng Yao ◽  
Jian Du
Keyword(s):  
Time Series ◽  
Time Delay ◽  
Order Approximation ◽  
Least Square Method ◽  
Least Square ◽  
Frequency Drift ◽  
Smoothing Process ◽  
Standard Profile ◽  
Estimation Of Time ◽  
Navigation Information

The original navigation information of XNAV is the arrival time series of X-ray photons received by spacecraft. The key issue is to estimate parameters,including time delay, frequency drift and change rate of the observed profile by comparing it with corresponding standard profile in “folding process”. This paper illustrates the equation of equiphase point in time series of photons, and gets the initial approximate value of time delay and frequency drift by Larsson cycle folding and coherent function methods. Higher-order approximation is obtained by least square method, and more precise value is calculated by cyclic iteration. Simulation result indicates our method can achieve high precision even without noise eliminating and smoothing process. The proposed method, maybe kind of complicate, it proves the feasibility of XNAV.

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