Results 191 to 200 of about 44,208 (243)

Optimization of fuzzy logic controller in the converter of a standalone solar power system using the firefly algorithm. [PDF]

Sci Rep
Nouri P, Kamarposhti MA, Nouri T, Radmehr M.   +3 more
europepmc   +1 more source

Enhancing MPPT performance of a grid-connected Doubly-Fed induction generator-based wind power plant using hybrid ANFIS-PI control strategy. [PDF]

Sci Rep
Biyazne LW, Tuka MB, Abebe YM, Wellhöfer A.   +3 more
europepmc   +1 more source

Fuzzy controller-driven pattern search optimization for a DC-DC boost converter to enhance photovoltaic MPPT performance. [PDF]

Sci Rep
Abdolrasol MGM, Tiong SK, Ker PJ, Ansari S, Ayob A, Shuaibu HA, Busaidi ASA, Ustun TS.   +7 more
europepmc   +1 more source

An improved T-S fuzzy controller for energy management of parallel hybrid vehicles. [PDF]

Sci Rep
Hokmabad ES, Rostami N, Sharifian MBB.
europepmc   +1 more source

Development of a Neural-Fuzzy-Based Variable Admittance Control Strategy for an Upper Limb Rehabilitation Exoskeleton. [PDF]

Sensors (Basel)
Shi Y, Li K, Zhang Y, Wu Q.
europepmc   +1 more source

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Fuzzy distance of triangular fuzzy numbers

Journal of Intelligent & Fuzzy Systems, 2013
In this paper, a new triangular fuzzy distance is proposed for two triangular fuzzy numbers and this distance is developed and applied for two points in a K-dimensional space. In this fuzzy distance we use the left and right point. Its calculations are easier compared to the previous presented distances and its result is always a non negative fuzzy ...
Sadi-Nezhad, Soheil, Noroozi-yadak, Ameneh, Makui, Ahmad   +2 more
openaire   +1 more source

Fuzzy SVM Based on Triangular Fuzzy Numbers

2007 International Conference on Machine Learning and Cybernetics, 2007
Support vector machine (SVM) is novel type learning machine, based on statistical learning theory, whose tasks involve classification, regression or novelty detection. Traditional SVM classifies the data with numerical features. However, in most cases of real world, there are much more data with fuzzy features.
Qiang He, Cong-Xin Wu, Eric C.C. Tsang
openaire   +1 more source

A NEW METHOD FOR RANKING TRIANGULAR FUZZY NUMBERS

International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems, 2012
The ranking and comparing of fuzzy numbers have important practical uses, such as in risk analysis problems, decision-making, optimization, forecasting, socioeconomic systems, control and certain other fuzzy application systems. Several methods for ranking fuzzy numbers have been widely-discussed though most of them have shortcomings.
Akyar, Emrah, Akyar, Handan, Düzce, Serkan Ali   +2 more
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RIDGE REGRESSION PROCEDURES FOR FUZZY MODELS USING TRIANGULAR FUZZY NUMBERS

International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems, 2004
This paper presents a new method of estimating fuzzy multivariable linear and nonlinear regression models using triangular fuzzy numbers. This estimation method is obtained by implementing a dual version of the ridge regression procedure for linear models.
Hong, Dug Hun, Hwang, Changha
openaire   +1 more source