Nile River Flow Forecasting Based Takagi-Sugeno Fuzzy Model

نویسندگان
چکیده

برای دانلود باید عضویت طلایی داشته باشید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Stable Indirect Adaptive Fuzzy Control Based on Takagi-sugeno Model

This paper presents an indirect adaptive fuzzy control scheme for nonlinear uncertain stable plants with unmeasurable states. A discrete-time T-S fuzzy model is employed as a dynamic model of an unknown plant. Based on this model, a feedback linearization controller is designed and applied to both the model and the plant. Parameters of the model are updated on-line to allow for partially unknow...

متن کامل

LMI-based tracking control for Takagi-Sugeno fuzzy model

This paper deals with the problem of tracking control for Takagi-Sugeno fuzzy model. An LMI (Linear Matrix Inequality) formulation is suggested to make possible the convergence of the state vector of the continuous-time system to a desired one using a new approach, called MultiQuadratic Fuzzy Lyapunov (MQFL). A fourth order unstable nonlinear system is studied to illustrate the efficiency of th...

متن کامل

Evolutionary Instance Selection Algorithm based on Takagi-Sugeno Fuzzy Model

In this study, we propose evolutionary instance selection based on the Takagi-Sugeno (T-S) fuzzy model. The previous neural network with weighted fuzzy membership functions (NEWFM) supports feature selection; thus, it enables the selection of minimum features with the highest performance. The enhanced NEWFM supports a weighted mean defuzzification in the T-S fuzzy model with a confidence interv...

متن کامل

Fuzzy model-based predictive control using Takagi-Sugeno models

Nonlinear model-based predictive control (MBPC) in multi-input multi-output (MIMO) process control is attractive for industry. However, two main problems need to be considered: (i) obtaining a good nonlinear model of the process, and (ii) applying the model for control purposes. In this paper, recent work focusing on the use of Takagi±Sugeno fuzzy models in combination with MBPC is described. F...

متن کامل

Financial Time-Series Forecasting based on a Neural Network with Weighted Fuzzy Membership Functions and the Takagi-Sugeno Fuzzy Model

This paper proposes financial time-series forecasting using a feature selection method based on the non-overlap area distribution measurement method supported in a neural network with weighted fuzzy membership functions (NEWFM) and the TakagiSugeno (T-S) fuzzy model. The non-overlap area distribution measurement method selects the minimum number of features with the highest performance by remov...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

ژورنال

عنوان ژورنال: Journal of Applied Sciences

سال: 2010

ISSN: 1812-5654

DOI: 10.3923/jas.2010.284.290