In this study, a Multi-Objective Genetic Algorithm (MOGA) is utilized to extract interpretable and compact fuzzy rule bases for modeling nonlinear Multi-input Multi-output (MIMO) systems. In the process of non- linear system identi cation, structure selection, parameter estimation, model performance and model validation are important objectives. Furthermore, se- curing low-level and high-level ...

in this paper, we investigate the existence of a positive solution of fully fuzzy linear equation systems. this paper mainly to discuss a new decomposition of a nonsingular fuzzy matrix, the symmetric times triangular (st) decomposition. by this decomposition, every nonsingular fuzzy matrix can be represented as a product of a fuzzy symmetric matrix s and a fuzzy triangular matrix t.

inventory control problem is one of the problems in decision making and management that contains non-crisp parameters in real world. economic production quantity (epq) model in fuzzy environment has been studied so far by many researchers. one of the main assumptions in all previous researches was neglecting the inventory shortage. in this research, a new multi-item epq model with fuzzy random ...

Supplier selection is a multi-criteria problem which includes both tangible and intangible factors in these problems if suppliers have capacity or other different constraints two problems will exist: which suppliers are the best and how much should be purchased from each selected supplier? The objective of this paper is to present an integrated model and a supporting approach for effective ...

this paper is concerned with the development of a novel classifier for automatic mass detection of mammograms, based on contourlet feature extraction in conjunction with statistical and fuzzy classifiers. in this method, mammograms are segmented into regions of interest (roi) in order to extract features including geometrical and contourlet coefficients. the extracted features benefit from...

Quality function deployment (QFD) is a customer-driven approach, widely used to develop or process new product to maximize customer satisfaction. Last researches used linear physical programming (LPP) procedure to optimize QFD; however, QFD issue involved uncertainties, or fuzziness, which requires taking them into account for more realistic study. In this paper, a set of fuzzy data is used to ...

The fuzzy linear regression model with fuzzy input-output data andcrisp coefficients is studied in this paper. A linear programmingmodel based on goal programming is proposed to calculate theregression coefficients. In contrast with most of the previous works, theproposed model takes into account the centers of fuzzy data as animportant feature as well as their spreads in the procedure ofconstr...