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Determining a suitable location for a Sewage Treatment Plant using a new fuzzy weighted average (FWA) method based on left and right scores
, Article 13th Iranian Conference on Fuzzy Systems, IFSC 2013 ; 2013 ; Sadrania, A ; Zibandeh, M ; Rostami, P ; Sharif University of Technology
IEEE Computer Society
2013
Abstract
Finding the most suitable location among some alternatives is one of the most important factors which could affect the whole success of the construction of a facility. The facility site selection is a multiple criteria decision making (MCDM) problem including both quantitative and qualitative criteria. Due to some difficulties in many real life cases, defining the exact values for MCDM problems is almost impractical and, it's preferable to use fuzzy values (fuzzy numbers) in this type of problems. In this study, we try to determine a suitable location for a Sewage Treatment Plant by using a new fuzzy weighted average (FWA) method. For this aim, ten different criteria is defined and then, by...
Novel adaptive Kalman filtering and fuzzy track fusion approach for real time applications
, Article 2008 3rd IEEE Conference on Industrial Electronics and Applications, ICIEA 2008, Singapore, 3 June 2008 through 5 June 2008 ; 2008 , Pages 120-125 ; 9781424417186 (ISBN) ; Sadati, N ; Sharif University of Technology
2008
Abstract
The track fusion combines individual tracks formed by different sensors. Tracks are usually obtained by Kalman Filter (KF), since it is suitable for real-time application. The KF is an optimal linear estimator when the measurement noise has a Gaussian distribution with known covariance. However, in practice, some of the sensors do not have these properties, and the traditional KF is not an optimal estimator. In this paper, a novel adaptive Kalman filter (NAKF) is proposed. In this approach, the measurement noise covariance is adjusted by using an introduced simple mathematical function of one variable, called the degree of matching (DoM), where it is defined on the basis of covariance...