In this section, the performance of the proposed roughfuzzy clustering algorithm1 is compared with that of hard c-means (HCM)2, fuzzy c-means (FCM)3, rough-fuzzy cmeans (RFCM)4, cluster identification via connectivity kernels (CLICK)5, and self organizing map (SOM)6 with respect to gene ontology. The performance of the normalized rangenormalized city block distance (NRNCBD) over Pearson distanc...

The Recent modern techniques, communication between humans and computers is proven a tremendous achievement in the field medical science. Computer hardware and signal processing have made possible the use of EEG signals or “brain waves” for Human-computer communication. Electroencephalography (EEG) is the electrical activity recording along the scalp. EEG refers to the recording of the spontane...

The size of web has increased exponentially over the past few years with thousands of documents related to a subject available to the user. With this much amount of information available, it is not possible to take the full advantage of the World Wide Web without having a proper framework to search through the available data. This requisite organization can be done in many ways. In this paper w...

this paper presents a fuzzy decision-making approach to deal with a clustering supplier problem in a supply chain system. during recent years, determining suitable suppliers in the supply chain has become a key strategic consideration. however, the nature of these decisions is usually complex and unstructured. in general, many quantitative and qualitative factors, such as quality, price, and fl...

The Demarcation and prediction of the area of the tumor have an important role in medical treatments of malignant tumors. This paper describes an application of Fuzzy set theory in medical image processing, namely brain tumor demarcation. Fuzzy C-Means is proved to be a good and efficient segmentation method. But the main disadvantage of this method is that it is highly sensitive to noise. In t...

In this paper we present an automatic algorithm for segmenting the putamen from brain MRI based on wavelets and neural network. We first locate the position of putamen using wavelet features. The fuzzy cmeans algorithm is then combined with edge detection to segment the grey matter pixels belonging to the putamen in the located region. Moment features are extracted from the segmented objects fo...

Many conventional contrast enhancement techniques adopt a global approach to enhance all the brightness level of the image. However, it is usually difficult to enhance all land cover classes appearing in the satellite images, because local contrast information and details may be lost in the dark and bright areas. In this study, a fuzzy-based image enhancement method is developed to partition th...

A successful Case-Based Reasoning (CBR) system highly depends on how to design an accurate and efficient case retrieval mechanism. In this research we propose a Weighted Feature C-means clustering algorithm (WF-Cmeans) to group all prior cases in the case base into several clusters. In WF-Cmeans, the weight of each feature is automatically adjusted based on the importance of the feature to clus...