Fuzzy clustering is well known as a robust and efficient way to reduce computation cost to obtain the better results. In the literature, many robust fuzzy clustering models have been presented such as Fuzzy C-Mean (FCM) and Possibilistic C-Mean (PCM), where these methods are Type-I Fuzzy clustering. Type-II Fuzzy sets, on the other hand, can provide better performance than Type-I Fuzzy sets, es...

The purpose of this article is to present a class of consumption sectors which exhibit a continuously differentiable mean demand although individual preferences are not assumed to be convex. As we have argued in an earlier paper [Dierker et al. (1980b, introduction)], several economic questions require mean demand to be a continuously differentiable function and not only to be a continuous one....

introduction: virtual bronchoscopy is a reliable and efficient diagnostic method for primary symptoms of lung cancer. the segmentation of airways from ct images is a critical step for numerous virtual bronchoscopy applications. materials and methods: to overcome the limitations of the fuzzy connectedness method, the proposed technique, called fuzzy connectivity - fuzzy c-mean (fc-fcm), utilized...

detection of brain tissues using magnetic resonance imaging (mri) is an active and challenging research area in computational neuroscience. brain mri artifacts lead to an uncertainty in pixel values. therefore, brain mri segmentation is a complicated concern which is tackled by a novel data fusion approach. the proposed algorithm has two main steps. in the first step the brain mri is divided to...

artificial recharge can be an effective method to raise the groundwater table and to resolve the groundwater crisis in sefid dasht plain. the most important step to successful accomplishment of artificial recharge is locating suitable areas for artificial recharge. hence this research carried out with purpose of determining suitable areas for artificial recharge in sefid dasht plain. slope, sur...