It is introduced an approach to the problem of "building logics" over sets of facts with only structured by a fuzzy relation of "consequence". Notions of "Truth" and "Falsehood" are introduced by means of two generalizations for classical Modus Ponens and Modus Tollens. Studying this concepts a theoretical base to explain the mode of reasoning in expert systems is obtained. By studying fuzzy tr...

This paper presents an attempt to introduce the concepts of fuzzy set theory in the design of web-based distance learning systems. A fuzzy decision making process is used to update the leaner model and specify his/her learning level to provide appropriate teaching materials to each learner. Such a system can deal with uncertainties in the learner’s degree of understanding in each unit. It provi...

Breast cancer is one of the most frequent occurring cancers in women throughout the world including U.K. The grading of this cancer plays a vital role in the prognosis of the disease. In this paper we present an overview of the use of advanced computational method of fuzzy inference system as a tool for the automation of breast cancer grading. A new spectral data set obtained from Fourier Trans...

Breast cancer is one of the most frequent occurring cancers in women throughout the world including U.K. The grading of this cancer plays a vital role in the prognosis of the disease. In this paper we present an overview of the use of advanced computational method of fuzzy inference system as a tool for the automation of breast cancer grading. A new spectral data set obtained from Fourier Trans...

This paper proposes a TSK-type Neuro-Fuzzy system tuned with a novel learning algorithm. The proposed algorithm used an improved version of the standard Particle Swarm Optimization algorithm, it employs several sub-swarms to explore the search space more efficiently. Each particle in a sub-swarm correct her position based on the best other positions, and the useful information is exchanged amon...

Multimodel approaches are widely used with linear submodels, but border areas around submodels are problematic. Special cases of fuzzy linguistic equation models, which can be understood as linguistic Takagi-Sugeno (LTS) type fuzzy models, can be used to solve these problems in many cases. These models use a special nonlinear scaling approach for both inputs and outputs. The LTS models are robu...

Group technology (GT) is a useful way to increase productivity with high quality in cellular manufacturing systems (CMSs), in which cell formation (CF) is a key step in the GT philosophy. When boundaries between groups are fuzzy, fuzzy clustering has been successfully adapted to solve the CF problem; however, it may result uneven distribution of parts/machines where the problem becomes larger. ...

Recently the applications of unmanned systems are steadily increasing. Unmanned Surface Vessels (USV) can be used for military and rescue purposes. This paper designs a Fuzzy-LQR controller for Heading control of the USV system. A new analysis of the fuzzy system behavior presented helps to make possible precise integration of LQR features into fuzzy control. This Fuzzy-LQR controller is used t...

This paper shows possibility of extraction Social, Group and Individual Mind from Multiple Agents Rule Bases. Types those Rule bases are selected as two fuzzy systems, namely Mambdani and Takagi-Sugeno fuzzy system. Their rule bases are describing (modeling) agent behavior. Modifying of agent behavior in the time varying environment will be provided by learning fuzzyneural networks and optimiza...

Network lifetime improvement and uncertainty in multiple systems are the issues of wireless sensor network routing. This paper presents fuzzy based particle swarm optimization routing technique to improve the network scalability. Significantly, in the cluster formation procedure, fuzzy based system is used to solve the uncertainty and network balancing. Cluster heads play an important role to r...