The aim of this work is to identify generic (multi-patient) models of the human Central Nervous System (CNS) control by means of the Fuzzy Inductive Reasoning (FIR) methodology. Previous works on this direction showed that FIR approach was able to capture in a reliable way the dynamic behavior of the CNS control for 5 diierent patients. For each one of them a fuzzy inductive model was identiied...

This paper presents a new neuro-fuzzy controller for robot manipulators. First, an inductive learning technique is applied to generate the required modelling rules from input/output measurements recorded in the off-line structure learning phase. Second, a fully differentiable fuzzy neural network is developed to construct the inverse dynamics part of the controller for the on-line parameter lea...

In this paper we study the problem of classification of textual web reports. We are specifically focused on situations in which structured information extracted from the reports is used for classification. We present an experimental classification system based on usage of third party linguistic analyzers, our previous work on web information extraction, and fuzzy inductive logic programming (fu...

In this paper we introduce a new notion of generalized metric, called i-metric. This generalization is made by changing the valuation space of the distance function. The result is an interesting distance function for the set of fuzzy numbers of Interval Type with non negative fuzzy numbers as values. This example of i-metric generates a topology in a very natural way, based on open balls. We pr...

Given a nonempty set X, a fuzzy ideal I on X is a collection of subsets of X closed under finite union and subset operations. In this paper we define a space to be locally I fuzzy compact space if every point in the space has an I fuzzy compact neighbourhood. Basic results concerning locally I fuzzy compact spaces are given relating to subspaces, preservation of functions, and products. Classic...

The inductive learning of a fuzzy rule-based classification system (FRBCS) with high interpretability is made difficult by the presence of a large number of features that increases the dimensionality of the problem being solved. The difficult comes from the exponential growth of the fuzzy rule search space with the increase in the number of features considered. In this work we tackle this probl...

This paper advances a fuzzy control strategy of the phase angle between the voltage and the current of a variable RL load using the system introduced in [3]. This control method is-easy to adapt for performance The paper presents a practical implementation of a fuzzy controller for the control of an induction motor. control of power factor in a circuit with variable inductive load using a switc...

The inductive learning of a fuzzy rule-based classification system (FRBCS) with high interpretability is made difficult by the presence of a large number of features that increases the dimensionality of the problem being solved. The difficult comes from the exponential growth of the fuzzy rule search space with the increase in the number of features considered. In this paper we propose a geneti...

Ngcibi, Murali and Makamba [Fuzzy subgroups of rank two abelian$p$-group, Iranian J. of Fuzzy Systems {bf 7} (2010), 149-153]considered the number of fuzzy subgroups of a finite abelian$p$-group $mathbb{Z}_{p^m}times mathbb{Z}_{p^n}$ of rank two, andgave explicit formulas for the cases when $m$ is any positiveinteger and $n=1,2,3$. Even though their method can be used for thecases when $n=4,5,l...

The problem of learning universally quantiied function free rst order Horn expressions is studied. Several models of learning from equivalence and membership queries are considered , including the model where interpretations are examples (Learning from Interpretations), the model where clauses are examples (Learning from Entailment), models where extensional or intentional background knowledge ...