Dealing with notions of health, illness and disease contains dealing with fuzziness. As the paper will demonstrate, states of these notions do not only exist or not exist. The medical philosopher and physician SadeghZadeh introduced the notions of fuzzy health, fuzzy illness and fuzzy disease. A closer look will be taken on the concept of fuzzy disease. Because there are different possibilities...

Intelligent software estimation models are need of the time. With increased development of Bayesian networks for software project management, one requires an explicit Bayesian Network (BN) to provide effort estimates based on historical data. This paper proposes a simple BN, based on classification approach. However the classes of ranges of size value, are distributed with help of fuzzification...

Advances in image and video processing algorithms and the availability of computational resources has paved the way for real-time medical decision support systems to be a reality. Video capsule endoscopy is a direct imaging method for gastrointestinal regions and produces large scale color video data. Fuzzification of color spaces can improve contextual description based tasks that are required...

This article presents a new technique to detect a premature atrial contraction (PAC). The technique employs a hybrid of particle swarm optimization (PSO) and fuzzy inference system (FIS), and is called PSO-FIS. In the detection electrocardiographic features are used for the inputs of PSO-FIS. In PSO-FIS, a PSO is used to find the optimal parameters of the FIS. A Gaussian function is employed fo...

This paper proposes a new hybrid time series forecasting system which is the fusion of the fuzzy system and the artificial neural network. The proposed fuzzy-neural system consists of 5 layers: the input layer, the fuzzification layer, the inference layer, the hidden layer, and the output layer. The artificial neural network is used as the fuzzy inference engine, while the genetic algorithm is ...

This paper discusses fuzzification of crisp domains into fuzzy classes providing fuzzy domains. Relationship between two fuzzy domains, Xi and Xj , is represented by a matrix, wij . If Xi and Xj have n and m elements of fuzzy data, respectively, then wij is n × m matrix. Our primary goal in this paper is to generate and provide some formulas for predicting interval probability in the relation t...

The vectors used in IR, whether to represent the documents or the terms, are high dimensional, and their dimensions increase as one approaches real problems. The algorithms used to manipulate them, however, consume enormously increasing amounts of computational capacity as the said dimension grows. We used the Kohonen algorithm and a fuzzification module to perform a fuzzy clustering of the ter...

Challenged by real-world clustering problems this paper proposes a novel fuzzy clustering scheme of datasets produced in the context of intuitionistic fuzzy set theory. More specifically, we introduce a variant of the Fuzzy C-Means (FCM) clustering algorithm that copes with uncertainty and a similarity measure between intuitionistic fuzzy sets, which is appropriately integrated in the clusterin...

We present a hybrid system for automatic analysis of clinical routine EEG, comprising a spectral analysis and an expert system. EEG raw data are transformed into the time-frequency domain by the so-called adaptive frequency decomposition. The resulting frequency components are converted into pseudo-linguistic facts via fuzzification. Finally, an expert system applies symbolic rules formulated b...