Neuro Fuzzy System (NFS)
A NOVEL PREPROCESSING SYSTEM USING EVOLUTIONARY NEURO FUZZY SYSTEM
... evolutionary neuro-fuzzy system (ENFS) is the result of adding evolutionary hunt procedures to systems, integrating fuzzy logic computing and neural ...with NFS, is that, the learning ...
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Implementation of Neuro Fuzzy System for Diagnosis of Multiple Sclerosis
... a neuro fuzzy system that learn how set data using fuzzy rules and fuzzy ...SEMG system was used for data acquisition and recording, then this raw electromyography (EMG) signals ...
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A Neuro Fuzzy System for Modeling the Depression Data
... proposed Neuro-Fuzzy ...the fuzzy membership function ...developed neuro-fuzzy system is explained layer-by-layer as shown in ...this system: I ij and O ij represent the ...
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The Implementation And Automation Of Software Reliability Assessment Model Using Neuro Fuzzy System
... In 2011, we propose an adaptive framework of incorporating path testing techniques into the reliability estimation for modular software systems. Three estimated methods based on common program structures are presented to ...
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Neuro Fuzzy System for Routing in a Computer Network
... client system, bandwidth table which represents the registered bandwidth in the system and the route table which specifies the delay for the entire ...
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Adaptive Neuro-Fuzzy System for Cancer
... Sakshi Maskara, is a research scholar in Computer Science Department at HRIT, Ghaziabad. She is perusing masters in computer science. Her research interests are in fuzzy logic networks and in medical problems ...
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Image Denoising Using Adaptive Neuro-Fuzzy System
... provide system output values for any given input values through an interpolation of all the relevant individual ...as neuro-fuzzy models appear as an attempt to merge the advantages of both systems ...
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Portfolio Investment Model Using Neuro Fuzzy System
... [5][6][7].A fuzzy logic system is good at modeling linguistic terms used in natural language by using a set of if-then rules and also it can deal with uncertainties very easily with higher ...
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Spike discharge prediction based on neuro-fuzzy system
... inference system (DENFIS), hybrid neural fuzzy inference system (HyFIS) and subtractive clustering and fuzzy c-means (SBC) algorithms and section 3 presents the performance of different ...
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Implementation of Computational Intelligent Techniques for Diagnosis of Cancer Using Digital Signal Processor
... ANNs are massively distributed parallel processing systems made up of highly interconnected neural computing elements that have the ability to learn and thereby acquire knowledge and make it available for use [17]. ...
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Article Description
... A neuro-fuzzy classifier is used to detect the abnormalities in the MRI brain ...the neuro-fuzzy classifier used is based on the ANFIS ...ANFIS system is a combination of neural network ...
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The Most General Intelligent Architectures of the Hybrid Neuro-Fuzzy Models
... the fuzzy logic and neural networks make them ideal solution in individual use for some kinds of artificial intelligent but not ...example, system modeling technique through the neural networks, is ...
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Online Full Text
... Solved neuro-fuzzy system seems to perform both the fundamental requirements of intelligent manufacturing, ...usual neuro-fuzzy models only with severe ...solved system is a good ...
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Neuro-Fuzzy Expert System For Diagnosis Of Thyroid Diseases
... the system were computed using a range of default values in which each condition of a Thyroid disease falls within, the range of values for Hypothyroidism is from values less than ...of neuro-fuzzy ...
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Threshold Neuro Fuzzy Expert System for Diagnosis of Breast Cancer
... using Neuro – Fuzzy classification method prepared by Ching-Hung ...of Fuzzy inference system and wavelet transform employed to decrease the number of missing regions or unnecessary ...of ...
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Power Factor Correction of Three Phase Diode Rectifier at Input Stage Using Artificial Intelligent Techniques for DC Drive Applications
... the fuzzy controller are output current and Error (e) in output ...the fuzzy controller is control signal CS. The fuzzy variables Negative Large (NL), Negative Medium (NM), Negative Small (NS), Zero ...
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Indirect Position Estimation of Switched Reluctance Motor based on Flux Sensing Method
... From the measured phase current and flux, the rotor position is estimated with the help of two types of controller algorithm. Depending upon the requirement the gain value is introduced. Then the comparator block compare ...
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A Multitarget Tracking Video System Based on Fuzzy and Neuro-Fuzzy Techniques
... So the association problem to solve is the decision of the most proper grouping of blobs and assignation to each track for each frame processed. The characteristics of data to be processed, blobs detected in image ...
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Adaptive Neuro Fuzzy Expert System for Diagnosing HIV
... expert system gives some symptoms from which the user needs to select ...the fuzzy expert system diagnosis diseases based on its Knowledge, add catalyst factor (if any), do ranking and gives the ...
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NEW MODEL TRANSFORMATION USING REQUIREMENT TRACEBILITY FROM REQUIREMENT TO UML BEHAVIORAL DESIGN
... In this paper, the performance of the hybrid intelligent controllers is compared with conventional PI controller. The simulation results show that the ANFIS controller based soft switching inverter is designed for BLDC ...
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