Fault diagnosis is essential for the reliable, safe, and efficient operation of the plant and for maintaining quality of the products in industrial system. This paper presents an ensemble fault diagnosis algorithm based on fuzzy c-means algorithm (FCM) with the Optimal Number of Clusters (ONC) and probabilistic neural network (PNN), called FCM-ONC-PNN. In clustering methods, the estimation of t...

Data clustering is one of the important data mining methods. It is a process of finding classes of a data set with most similarity in the same class and most dissimilarity between different classes. The well known hard clustering algorithm (K -means) and Fuzzy clustering algorithm (FCM) are mostly based on Euclidean distance measure. In this paper, a comparative study of these algorithms with d...

Up to now, several algorithms for clustering large data sets have been presented. Most clustering approaches for data sets are the crisp ones, which cannot be well suitable to the fuzzy case. In this paper, the authors explore a single pass approach to fuzzy possibilistic clustering over large data set. The basic idea of the proposed approach (weighted fuzzy-possibilistic c-means, WFPCM) is to ...

This paper presents fuzzy clustering algorithms for mixed features of symbolic and fuzzy data. El-Sonbaty and Ismail proposed fuzzy c-means (FCM) clustering for symbolic data and Hathaway et al. proposed FCM for fuzzy data. In this paper we give a modi3ed dissimilarity measure for symbolic and fuzzy data and then give FCM clustering algorithms for these mixed data types. Numerical examples and ...

Soft Clustering plays a very important rule on clustering real world data where a data item contributes to more than one cluster. Fuzzy logic based algorithms are always suitable for performing soft clustering tasks. Fuzzy C Means (FCM) algorithm is a very popular fuzzy logic based algorithm. In case of fuzzy logic based algorithm, the parameter like exponent for the partition matrix that we ha...

In recent past, vector quantization has been observed as an efficient technique for image compression. In general, image compression reduces the number bits required to represent an image. The main significance of image compression is that the quality of the image is preserved. This in turn increases the storage space and thereby the volume of the data that can be stored. Image compression is t...

Fuzzy c-means (FCM) clustering has been widely used in image segmentation. However, in spite of its computational efficiency and wide spread popularity, the FCM algorithm does not take the spatial information of pixels into consideration, and hence may result in low robustness to noise and less accurate segmentation. In this paper, a modified adaptive fuzzy c-means clustering (AFCM) algorithm i...

The image segmentation performance of any clustering algorithm is sensitive to the features used and the types of object in an image, both of which compromise the overall generality of the algorithm. This paper proposes a novel fuzzy image segmentation considering surface characteristics and feature set selection strategy (FISFS) algorithm which addresses these issues. Features that are exploit...

هلاقم تاعلاطا هدیکچ لماک یشهوژپ هلاقم :تفایرد 23 دنفسا 1392 :شریذپ 15 تشهبیدرا 1393 :تیاس رد هئارا 19 رهم 1393 رد اب هلاقم نیا رد يور مسج لمح يارب ریسم بیقعت یقیبطت لرتنک ،مسج نتفرگ نیح رد مسج و تابر کی هجنپ نیب شزغل ناکما نتفرگ رظن کت تابر کی طسوت نیمز رارق یسررب دروم یتشگنا یسررب يارب یبسانم هنومن ،متسیس نیا .تسا هتفرگ شور ياه فلتخم لیلحت دننام یحارط لرتنک هدننک اه رد تابر متسیس ماسجا ...