Fuzzy Inference
Load Balancing Using Fuzzy Inference System in Distributed Computing
... In this paper a load balancing technique using fuzzy inference system is discussed. Our method for balancing the load in the network can be used for both inter and intra cluster nodes. The two parameter ...
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NFI: a neuro-fuzzy inference method for transductive reasoning
... neural fuzzy inference method—NFI for transductive reasoning ...neuro-fuzzy inference systems for both online and offline time series prediction ...
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Evaluation of Students Performance using Hierarchical Fuzzy Inference System
... of fuzzy inference system for ...Hierarchical Fuzzy Inference System (HFIS) was used to reduce these rules at the same time preserve the accuracy behind the ...
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A sugeno and tsukamoto fuzzy inference system for denoising medical images
... type fuzzy inference system for noise filtering in medical images is ...two fuzzy filters and a post processor The proposed method is suitable for various types of noisy images and it is highly ...
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Medical decision support system using Fuzzy Cognitive Mapping& Fuzzy Inference System
... Fuzzy inference systems (FIS), also referred to as fuzzy models, are nonlinear black-box models that describe the relation between the inputs and the output of a real system using a set of ...
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Interval Type-2 TSK+ Fuzzy Inference System
... Fuzzy inference systems are mechanisms that use fuzzy logic and fuzzy set theory to map inputs and outputs, which has been successfully applied in many application areas, such as decision ...
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Fuzzy integral for rule aggregation in fuzzy inference systems
... The fuzzy inference system (FIS) has been tuned and re- vamped many times over and applied to numerous ...the fuzzy integral, a parametric non-linear aggregation operator, can be used to fill this ...
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Dynamic-link rule base in fuzzy inference system
... A dynamic-link rule base (DLRB) was introduced into the conventional fuzzy inference system for the purpose of dynamically skipping the unfired rules and linking the f[r] ...
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Palmprint Identification Based on Adaptive Neuro Fuzzy Inference System
... pattern. Fuzzy logic is a problem solving mechanism that has received wide ...clustering fuzzy logic is considered. Fuzzy logic provides an easy and simple way to draw a definite conclusion from ...
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The SIRM Fuzzy Inference System: A Study of its Suitability
... new fuzzy inference model, SIRMs (Single Input Rule Modules) Connected Fuzzy Inference Model [Yubazaki et ...input fuzzy rule module is ...conventional fuzzy inference ...
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A Credit Rating Model in a Fuzzy Inference System Environment
... Abstract: One of the most important functions of an export credit agency (ECA) is to act as an intermediary between national governments and exporters. These organizations provide financing to reduce the political and ...
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Development of Fuzzy Inference Scheme for LC Oscillator Design
... used FUZZY TOOLBOX of MATLAB. The fuzzy approach can closely resemble the human thinking and hence some kind of decision making is possible under imprecise design data ...the FUZZY TOOLBOX ...
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USING FUZZY INFERENCE SYSTEMS TO OPTIMIZE HIGHWAY ALIGNMENTS
... The fuzzy inference process involves all the elements of Membership Functions, Logical Operations, and If-Then ...1975). Fuzzy inference systems have been successfully applied in fields such ...
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Fuzzy Inference with Parameter Identification for Indoor WLAN Positioning
... like fuzzy logic [19] in wireless indoor ...of fuzzy inference system and the other one advocates a fuzzy clustering related approach, especially fuzzy c-means ...some fuzzy ...
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Adoptive Neuro Fuzzy Inference System for Traffic Noise Prediction
... neuro-fuzzy inference system (ANFIS) is the implementation of fuzzy inference system (FIS) to adaptive networks for developing fuzzy rules with suitable membership functions to have ...
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Fuzzy Inference System Mamdani to Predicting Conformational Epitope Location
... Abstract -- Predicting of conformational epitope is one of the major challenge in the field of vaccine design. Several methods have been developed for predicting conformational epitope but that methods have mostly been ...
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Prioritization of Sustainable Production Indicators Using Fuzzy Inference System
... In Table2 for better illustration of rules, criteria of universality and importance was considered and shown two by two. For example, when the input parameters have average importance and output parameters have low ...
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Fuzzy Inference System for Edge Detection in Flat Electroencephalography Image
... the clusters. However, one of the clusters appears in brighter intensity than the other one. It shows that the morphological operator managed to identify the clusters but in different level of brightness. Meanwhile, ...
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Image Enhancement Using Adaptive Neuro-Fuzzy Inference System
... the fuzzy inference mechanism of the neuro- fuzzy ...type fuzzy system [49] with one input and one output. In neuro-fuzzy network, there are two types of fuzzy inference ...
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Image Enhancement using Hybrid Fuzzy Inference System (IEHFS)
... hybrid Fuzzy inference system is applied by taking a movable window over the image of 5 x 5 size, where the pixels around the center pixel are named according to the direction to identify ...the ...
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