In this paper, a comprehensive survey on various applications of Fuzzy Logic system has been carried out. GPU (Graphics Processing Units) is used for speed up purpose, otherwise commonly used for graphics applications. However, recent trends show use of GPU in various other general computational applications to run them parallel to reduce overall execution time. In this paper, it is discussed t...

The paper presents the potential of fuzzy logic (FL-I) and neural network techniques (ANN-I) for predicting the compressive strength, for SCC mixtures. Six input parameters that is contents of cement, sand, coarse aggregate, fly ash, superplasticizer percentage and water-to-binder ratio and an output parameter i.e. 28day compressive strength for ANN-I and FL-I are used for modeling. The fuzzy l...

Fuzzy Description Logics are a family of logics which allow to deal with structured knowledge affected by vagueness. Although a relatively important amount of work has been carried out in the last years, current fuzzy DLs are open to be extend with several features worked out in the fuzzy logic literature. In this work, we extend fuzzy DLs with fuzzy truth values, allowing to state sentences su...

Fuzzy logic control systems are structured numerical estimators. They combine both the numerical process and human like reasoning. Neural networks are numerical trainable dynamical systems that are able to emulate human brain functions; their connectionist structure can be used to find the proper parameters and structures that resemble human thinking rules for fuzzy logic controllers. Generally...

Disease forecasting using soft computing techniques is major area of research in data mining in recent years. To classify heart and diabetes diseases, this paper proposes a diagnosis system using cuckoo search optimized rough sets based attribute reduction and fuzzy logic system. The disease prediction is done as per the following steps 1) feature reduction using cuckoo search with rough set th...

Planning resources for a supply chain is a major factor determining its success or failure. In this paper we introduce an Interval Type-2 Fuzzy Logic model of a distribution network. It is believed that the additional degree of uncertainty provided by Interval Type-2 Fuzzy Logic will allow for better representation of the uncertainty and vagueness present in resource planning models. First, the...

This paper exemplifies the implementation of an efficient Information Retrieval (IR) System to compute the similarity between a dataset and a query using Fuzzy Logic. TREC dataset has been used for the same purpose. The dataset is parsed to generate keywords index which is used for the similarity comparison with the user query. Each query is assigned a score value based on its fuzzy similarity ...

This paper investigates and compares performance of various conventional and fuzzy logic based controllers at generator locations for oscillation damping. Performance of combination of conventional and fuzzy logic based controllers also studied by comparing overshoot on the active power deviation response for a small disturbance and damping ratio of the critical mode. Fuzzy logic based controll...

Processcapabilityindicesareusedtoevaluatetheperformanceofthemanufacturingprocess.When thespecificationlimitsandthetargetvaluearenotprecise,theauthorscannotusethetraditional methodstoassessthecapabilityoftheprocess.Fortheprocesseswithasymmetrictoleranceintervals, somefuzzyprocesscapabilityindiceshavebeenintroducedsuchas  Cpk '' and  Cpmk...

Fuzzy Logic Systems are widely recognized to be successful at modelling uncertainty in a large variety of applications. While recently interval type-2 fuzzy logic has been credited for the ability to better deal with large amounts of uncertainty, general type2 fuzzy logic has been a steadily growing research area. All fuzzy logic systems require the accurate specification of the membership func...