The purpose of multicriteria clustering is to locate groups alternatives that have comparable qualities and been examined across multiple criteria. An ordered profile a well-known problem, the fuzzy c-means (FCM) technique one most broadly used in every field life. At present, FCM for partitioning information into numerous clusters which are still lacking priority relations. To address problem ...

Recognizing TimeML events and identifying their attributes, are important tasks in natural language processing (NLP). Several NLP applications like question answering, information retrieval, summarization, and temporal information extraction need to have some knowledge about events of the input documents. Existing methods developed for this task are restricted to limited number of languages, an...

The fuzzy c-means (FCM) clustering algorithm is the best known and used method in fuzzy clustering and is generally applied to well defined set of data. In this paper a generalized Probabilistic fuzzy c-means (FCM) algorithm is proposed and applied to clustering fuzzy sets. This technique leads to a fuzzy partition of the fuzzy rules, one for each cluster, which corresponds to a new set of fuzz...

As special aggregation functions, overlap functions have been widely used in the soft computing field. In this work, with aid of two new groups fuzzy mathematical morphology (FMM) operators were proposed and applied to image processing, they obtained better results than existing algorithms. First, based on structuring elements, first group FMM (called OSFMM operators) was proposed, their proper...

The analysis and processing of large data are a challenge for researchers. Several approaches have been used to model these complex data, and they are based on some mathematical theories: fuzzy, probabilistic, possibilistic, and evidence theories. In this work, we propose a new unsupervised classification approach that combines the fuzzy and possibilistic theories; our purpose is to overcome th...

In this paper we present an hybrid approach which integrate Fuzzy C-Means (FCM) algorithms and Genetic Algorithms (GAs) to design an optimal classifier for the specific classification problem. This integration allows automatic generation of an classifier system, with an optimized subset of features, from a database of examples. The generated classifier strongly outperform the classic FCM algori...

In this study, Four Wave Mixing (FWM) characteristics in photonic crystal fibers are investigated. The effect of channel spacing, phase mismatching, and fiber length on FWM efficiency have been studied. The variation of idler frequency which obtained by this technique with pumping and signal wavelengths has been discussed. The effect of fiber dispersion has been taken into account; we obtain th...

يمومع باي تيعقوم متسيس كي تقد 3 رد متسيس وردوخ يربوان ياه يم ريثأت يفلتخم لماوع زا زا تـسا مزلا لـيلد نيمه هب و دريذپ شور دومن هدافتسا وردوخ هدش نييعت تيعقوم رد تقد شيازفا تهج هشقن قيبطت ياه . متسيس رد هشقن قيبطت وردوـخ يربواـن ياـه دراد هدهع رب ار رهش هشقن يوررب وردوخ يلعف تيعقوم نييعت هفيظو . رد هـشقن قيبطت هلأسم لح يارب يبيكرت متيروگلا كي هلاقم نيا متسيس رد يم داهنشيپ وردوخ يربوان يا...

Protein sequence motifs are very important to the analysis of biologically significant conserved regions to determine the conformation, function and activities of the proteins. These sequence motifs are identified from protein sequence segments generated from large number of protein sequences. All generated sequence segments may not yield potential motif patterns. In this paper, short recurring...