abstract regarding the imprecise or fuzzy data on the agriculture activities, applying models based on fuzzy data may be useful. in line with this condition this study tries to compare the ability of possiblistic programming approach in developing optimal solution with fuzzy and deterministic programming. to get this objective a data set obtained from 90 farmers of kohgilooye region, gathered i...

Data validation for models with errors in the variables is an important aspect for supporting decision making. In this context, several concepts have been employed. In this paper, we compare a possiblistic and a probabilistic approach. The DuPont Business model is chosen as an example for a controlling model with errors. Although the FuzzyCalc algorithm, representing the possiblistic approach, ...

In this paper, we propose new fuzzy c-means method for improving the magnetic resonance imaging (MRI) segmentation. The proposed method called “possiblistic fuzzy c-means (PFCM)” which hybrids the fuzzy c-means (FCM) and possiblistic c-means (PCM) functions. It is realized by modifying the objective function of the conventional PCM algorithm with Gaussian exponent weights to produce memberships...

Greenhouse gas (GHG) emissions from municipal solid waste (MSW) management significantly contribute to high global warming potential (GWP). However, most studies have failed to facilitate identifying MSW management schemes capable of comprehensively meeting the goals from decision-makers at different hierarchical levels under uncertainties. This study develops an inexact bi-level linear program...

Segmentation in image processing refers to the process of partitioning a digital image into multiple segments. This paper makes an attempt to segment the Comic images for extraction the text. Segmentation of comic images into extract the text is a challenging task primarily because of complexity of the structural Features like color, shape and texture. In this paper we proposed a color based co...

Uncertainty is a pervasive in real world environment due to vagueness, is associated with the difficulty of making sharp distinctions and ambiguity, is associated with situations in which the choices among several precise alternatives cannot be perfectly resolved. Analysis of large collections of uncertain data is a primary task in the real world applications, because data is incomplete, inaccu...