Regression analysis is an area of statistics that deals with the investigation of the dependence of a variable upon one or more variables. Recently, much research has studied fuzzy estimation. There are some approaches existing in the literature for the estimation of the fuzzy regression model. Two of them are frequently used in parameter estimation, one of which is proposed by Tanaka et al [21...

An adaptive Fuzzy Inference Perceptual model has been proposed for watermarking of digital images. The model depends on the human visual characteristics of image sub-regions in the frequency multi-resolution wavelet domain. In the proposed model, a multi-variable fuzzy based architecture has been designed to produce a perceptual membership degree for both candidate embedding sub-regions and str...

In this article authors presented selected methods of risk factors and safety estimation in air transport including use of fuzzy logic inference systems (fuzzy expert inference systems are under consideration) Keywords—safety; aviation; risk factors; fuzzy inference systems.

System modelling based on conventional mathematical tools like differential equations is not well suited for dealing with ill-defined and uncertain systems. By contrast, a fuzzy inference system, employing fuzzy if–then rules can model the qualitative aspects of human knowledge and reasoning processes without employing precise quantitative analyses. This fuzzy modeling or fuzzy identification e...

Fuzzy techniques may be used to represent uncertainty in both data and knowledge, and fuzzy inference systems (FISs) may be used to reason with such uncertain data and knowledge. In this paper, definitions are first provided for conventional type-1 fuzzy sets, more complex type-2 fuzzy sets and the recently introduced non-stationary fuzzy sets. Two medical applications in which such fuzzy sets ...

Fuzzy inference models can conduct advanced inference using knowledge which is easily understood by humans. In this paper, we propose a fuzzy inference model for learning based on experiences. The proposed model executes learning with input/output (I/O) data of the model and their evaluations obtained by trial-and-error of a task. Such a learning is executed after each end of a trial. Hence, it...

grid computing is a term referring to the combination of computer resources from multiple administrative domains to reach a common computational platform. mobile computing is a generic word that introduces using of movable, handheld devices with wireless communication, for processing data. mobile computing focused on providing access to data, information, services and communications anywhere an...