The paper presents fuzzy navigation system for a mobile robot. This navigation is based on fuzzy inference machine that performs path planning and obstacle avoidance in arbitrary complex environments. The system is built as two-level hierarchical system. On the higher level there is a controlling PC that is connected with robot control unit through duplex, wireless communication channel. A sens...

Introduction: The adaptive neuro-fuzzy inference system (ANFIS) is a soft computing model based on neural network precision and fuzzy decision-making advantages, which can highly facilitate diagnostic modeling. In this study we used this model in breast cancer detection. Methodology: A set of 1,508 records on cancerous and non-cancerous participant’s risk factors was used.  First,...

A novel recurrent neurofuzzy network is proposed in this paper. More specifically, in this work we generalize the recurrent neurofuzzy network structure proposed in [1], which is in turn is an improvement of the feedforward structure introduced in [2]. The network structure is composed by two structures: a fuzzy inference system and a neural network. The fuzzy inference system contains fuzzy ne...

This paper presents a proposition of the knowledge representation and the inference procedure including two types of uncertainty: probabilistic and fuzzy. Added weights to the fuzzy rule-based model state probabilities of fuzzy events in antecedents and consequents. The exemplary calculations are presented. Key-Words: Fuzzy sets, Knowledge representation, Inference procedure, Probability of fuz...

in this paper a non linear integrated fuzzy multi-objective production planning model with the labor learning and machines deterioration effects is presented. the objective function consists of two quantitative objectives namely increase profits and reduces the cost of system failure and a qualitative objective namely increases the satisfaction rate of the customers. different weights for objec...

Qualitative modeling may be applied when knowledge about a system is only available in linguistic form. The knowledge might be processed by a dynamic fuzzy system consisting of a rule base and an inference method modeling human reasoning. Conventional fuzzy inference methods do not consider this association to human reasoning and therefore are not suitable for the dynamic processing of linguist...

EDF is a classic dynamic embedded realtime multi-task scheduling algorithm. In an embedded soft real-time system, the deadline missing ratio is an important metric to evaluate system performance. When an embedded soft realtime system is overloaded, EDF algorithm is not effective. Considering the unsteadiness and unpredictability of a practical task running environment due to the unsteadiness of...

fuzzy controllers are being used in various control schemes. the aim of this work was adjusting hemodialysis machine parameters utilizing a fuzzy logic controller (flc) so that patient’s hemodynamic condition remains stable during hemodialysis treatment. for this purpose a comprehensive mathematical model of the arterial pressure response during hemodialysis, including hemodynamic, osmotic, and...

This paper presents the design of a VLSI fuzzy processor, which is capable of dealing with complex fuzzy inference systems, i.e., fuzzy inferences that include rule chaining. The architecture of the processor is based on a computational model whose main features are: the capability to cope effectively with complex fuzzy inference systems; a detection phase of the rule with a positive degree of ...

The present paper aimed at developing an approach based on Fuzzy Inference System (FIS) for measuring of knowledge sharing in the organization. In recent years there has been increasing interest in the knowledge sharing by experts and managers in the world, according to increasing importance of knowledge as the key source of competitive advantage, organizations have made serious effort to find ...