يا هچروم يدنب هشوخ متيروگلا ياراد پ ا ار يددعتم ياهرتم هلمج زا ،نتشادرب هب طوبرم ياهرتماراپ نتشاذگ اه هداد ديد عاعش ، يم هك دشاب ريثات و دنراد متيروگلا ييارگمه و دركلمع رد يدايز اطخ و شيامزآ تروص هب لاومعم نييعت يم رگ د دن . شور هلاقم نيا رد ي رب ينتبم CLA-PSO 1 ي هتسسگ لدم كي هك PSO دشاب يم يارب قيبطت كيتاموتا پ ياهرتمارا يا هچروم يدنب هشوخ يم داهنشيپ ددرگ . روظنم هب گلا ساسا رب هك د...

This paper presents a comparison of the three fuzzy based image segmentation methods namely Fuzzy C-Means (FCM), TYPE-II Fuzzy C-Means (T2FCM), and Intuitionistic Fuzzy C-Means (IFCM) for digital images with varied levels of noise. Apart from qualitative performance, the paper also presents quantitative analysis of these three algorithms using four validity functions-Partition coefficient (Vpc)...

Keywords: Cluster analysis Fuzzy clustering Fuzzy c-means (FCM) Initialization Bias correction Probability weight a b s t r a c t Fuzzy clustering is generally an extension of hard clustering and it is based on fuzzy membership partitions. In fuzzy clustering, the fuzzy c-means (FCM) algorithm is the most commonly used clustering method. Numerous studies have presented various generalizations o...

In the computer aided medical image process, image segmentation is always required as a preprocess stage. Fuzzy c-means (FCM) clustering algorithm has been commonly used in many medical image segmentations, particularly in the analysis of magnetic resonance (MR) brain image. However, all of these FCM methods are computation consuming that is difficult to be used in real time application. In the...

كچ ي هد فده و هقباس : شبات ،هتشذگ ههد لوط رد ناديم زا يشان يريگ نتنآ زا لصاح يسيطانغمورتكلا ياه هدـنريگ ياه / ت هدنتسرف تسا هتفاي شيازفا هارمه نفل . هعلاطم نيا In vivo جاوما رثا يسررب روظنم هب 950 نـفلت متسيس زترهاگم هارمه GSM ينلاوط تيوقت رب تدم ) LTP ( هيحان Dentate gyrus تفرگ تروص . شور و داوم اه : 32 ر أ داژن زا ركذم يهاگشيامزآ گرزب شوم س Wistar دودح ينس اب 3 نزو و هام 15 ± 220 ـ گ ،مر...

Image segmentation is a vital part of image processing. Segmentation has its application widespread in the field of medical images in order to diagnose curious diseases. The same medical images can be segmented manually. But the accuracy of image segmentation using the segmentation algorithms is more when compared with the manual segmentation. In the field of medical diagnosis an extensive dive...

This article presents a study of academic performance evaluation using soft computing techniques inspired by the successful application of K-means, fuzzy C-means (FCM), subtractive clustering (SC), hybrid subtractive clustering-fuzzy C-means (SC-FCM) and hybrid subtractive clustering-adaptive neuro fuzzy inference system (SC-ANFIS) methods for solving academic performance evaluation problems. M...

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Semi-supervised learning is somewhere between unsupervised and supervised learning. In fact, most semi-supervised learning strategies are based on extending either unsupervised or supervised learning to include additional information typical of the other learning paradigm. Constraint fuzzy c-means a novel semi-supervised fuzzy c-means algorithm proposed by Li et al [1]. Constraint FCM like FCM ...