One of the common problems for fuzzy system implementation arises from the complications of the fuzzy inference process. Extra computations are required to deduce a consequence due to nature of fuzzy sets. Furthermore, considerable simulations need to be performed to verify system functions. In order to reduce the prototyping time, the fuzzy system is partitioned into hardware and software port...

Among the many desirable properties of fuzzy inference systems not all of them are known to co-exist. For instance, a system based on a monotone fuzzy rule base need not be monotonic and interpolative simultaneously. Recently, Štěpnička and De Baets have investigated and shown the co-existence of the above two properties in the case of a fuzzy relational inference systems and the single-input-s...

introduction bacterial meningitis is a known infectious disease which occurs at early ages and should be promptly diagnosed and treated. bacterial and aseptic meningitis are hard to be distinguished. therefore, physicians should be highly informed and experienced in this area. the main aim of this study was to suggest a system for distinguishing between bacterial and aseptic meningitis, using f...

ABSTRACT-This paper proposed a control scheme based on fuzzy logic for a methanol water system of bubble cap distillation column. Fuzzy rule base and Inference System of fuzzy (FIS) is planned to regulate the reflux ratio (manipulated variable) to obtain the preferred product composition (methanol) for a distillation column. Comparisons are made with conventional controller and the results conf...

This paper presents an approach to similarity based approximate reasoning that elucidates the connection between similarity and existing approaches to inference in approximate reasoning methodology. A set of axioms is proposed to compute a reasonable measure of similarity between two fuzzy sets. Such a measure of similarity is then used at different stages to derive a conclusion in approximate ...

In this paper, a Sequential Adaptive Fuzzy Inference System called SAFIS is developed based on the functional equivalence between a radial basis function network and a fuzzy inference system (FIS). In SAFIS, the concept of “Influence” of a fuzzy rule is introduced and using this the fuzzy rules are added or removed based on the input data received so far. If the input data do not warrant adding...

This paper discusses a method for improving accuracy of fuzzy-rule-based classifiers using particle swarm optimization (PSO). Two different fuzzy classifiers are considered and optimized. The first classifier is based on Mamdani fuzzy inference system (M_PSO fuzzy classifier). The second classifier is based on TakagiSugeno fuzzy inference system (TS_PSO fuzzy classifier). The parameters of the ...

fuzzy logic has a high potential for managing the uncertainty sources associated with the medical expert systems. application of fuzzy inference model has been widely concentrated for managing uncertainties in computer based practices of medicine. this paper has proposed two fuzzy expert systems for prognosis of the heart disease based on: 1) mamdani inference model, and 2) sugeno inference mod...

The aim of this study is to employ the novel Adaptive Network-based Fuzzy Inference System to optimize the torque applied on the knee link of a rehabilitation robot. Given the special conditions of stroke or spinal cord injury patients, devices with minimum error are required for performing the rehabilitation exercises. After examining the anthropometric data tables of human body, parameters su...