Fuzzy linear parameter estimation algorithms: a new formulation

In this paper, we present a new formulation of a fuzzy linear estimation problem as one of the linear programming where the objective is to minimize the spread of the data points, subject to constraints on each measurement point to guarantee that the original membership is included in the estimated...

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Vydané v:International journal of electrical power & energy systems Ročník 24; číslo 5; s. 415 - 420
Hlavní autori: Soliman, S.A., Alammari, R.A., Temraz, H.K., El-Hawary, M.E.
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: Oxford Elsevier Ltd 01.06.2002
Elsevier
Predmet:
Applied sciences
Electrical engineering. Electrical power engineering
Electrical lead estimation
Electrical power engineering
Exact sciences and technology
Fuzzy parameters
Linear programming
Optimization
Power networks and lines
Linear programming
Fuzzy parameters
Electrical lead estimation
Optimization
Substation
Parameter estimation
Electric charge
Linear regression
Optimization method
Linear model
Case study
Fuzzy logic
Experimental result
Fuzzy algorithm
Electrical network
Busbar
Numerical simulation
Linear estimation
Fuzzy number
ISSN:0142-0615, 1879-3517
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Popis
Shrnutí:In this paper, we present a new formulation of a fuzzy linear estimation problem as one of the linear programming where the objective is to minimize the spread of the data points, subject to constraints on each measurement point to guarantee that the original membership is included in the estimated membership. Different models are developed based on fuzzy triangular membership as well as fuzzy numbers of LR-type, and applied to different examples in fuzzy linear regression and finally we apply these models for estimating the electrical load on a substation busbar. It is demonstrated that since the nature of the load is characterized by uncertainty, the proposed technique is well suited to apply for electrical load estimation.
ISSN:0142-0615
1879-3517
DOI:10.1016/S0142-0615(01)00033-3