fuzzy neural network approaches
International Journal of Emerging Technology and Advanced Engineering
... novel approaches are compared to embed watermark into the host image using quantization based on Back Propagation Neural Network (BPNN), and Dynamic Fuzzy Inference System ...propagation ...
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A Survey of Image Segmentation Methods using Conventional and Soft Computing Techniques for Color Images
... like network which perform color image segmentation using multilevel ...technique. Neural network is used to find multiple objects in the ...The network consists of three layers such as input ...
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Automatic Heart Disease Diagnosis System Based on Artificial Neural Network (ANN) and Adaptive Neuro Fuzzy Inference Systems (ANFIS) Approaches
... trained Neural Network and Neuro-Fuzzy, and the second at the testing module, where the testing data set is tested against the trained Neural Network and ...
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Intelligent Techniques for Modeling the Relationships between Sensory Attributes and Instrumental Measurements of Knitted Fabrics
... computing approaches, namely artificial neural network (ANN) and fuzzy inference system (FIS), have been applied to model the relationship between sensory properties and instrumental ...
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Forecasting on Crude Palm Oil Prices Using Artificial Intelligence Approaches
... forecasting approaches in predicting the CPO prices is becoming the matter into ...intelligence approaches, has been used namely artificial neural network (ANN) and adaptive neuro fuzzy ...
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Water level forecasting through fuzzy logic and artificial neural network approaches
... Finally, as regards the reliability aspect, none of the FL models present any failure when the DRI input data sets are used. In fact, differently from the ARI input data set, both fuzzy rule systems always furnish ...
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Adaptive Neuro-Fuzzy Systems
... of fuzzy model, two different phases must be carried out in fuzzy modeling, designated as structural and parametric ...of fuzzy sets used to partition each variable in the input and output space so ...
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Multi-Input Multi-Output Direct Adaptive Control for a Distributed Parameter Flexible Rotating Arm
... which fuzzy modeling, neural network approximation and energy-based approaches are used, in combination with adaptation mechanisms, to adjust neural network weights [33], to tune ...
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A Study of Image Classification using Machine learning-A Systematic Approach Aswathythankachan, Bino Thomas Abstract PDF IJIRMET1604010013
... Abstract : Machine learning is an application of artificial intelligence that make the computer to learn by themselves without being explicitly programmed. There are different classification techniques. like supervised ...
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A chemical-reaction-optimization-based neuro-fuzzy hybrid network for stock closing price prediction
... Early approaches to realistically solving this problem by observing the hidden laws of real stock index data were based on verities in statistical and computational models (Zhang, 2003; Adhikari & Agrawal, ...
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Framework for a Genetic-Neuro-Fuzzy Inferential System for Diagnosis of Diabetes Mellitus
... modern society is diabetes mellitus and it is not only a medical problem but also a socio-economy. Artificial Intelligence techniques have been successfully employed in diabetes disease diagnosis, risk evaluation, ...
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Cancer Diagnosis Using Fuzzy Min-Max Neural Network WithRule Extraction
... Artificial Neural Network (ANN) has emerged as an research applications tool including classification and regression [1][2] ...of neural network: ...
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Artificial Intelligence and its Application as an Integrated Approach
... The human brain is composed of 86 billion nerve cells called neurons. They are connected to other thousand cells by Axons. Stimuli from external environment or inputs from sensory organs are accepted by dendrites. These ...
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Neural Network Regressions with Fuzzy Clustering
... the fuzzy weighting ...the neural network part of Sarkar’s study and the derivation for a simple three-layer network with logistic transfer function is in Appendix ...this fuzzy mean ...
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Fuzzy Neural Network for Clustering and Classification
... days fuzzy logic and neural network are greatly used to develop intelligent systems ...combine fuzzy logic and neural network is that fuzzy logic have greater ability to ...
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Adaptive Neuro-Fuzzy Inference System based control of six DOF robot manipulator
... uncertainties. Fuzzy Logic Controller can very well describe the desired system behavior with simple “if-then” relations owing the designer to derive “if-then” rules manually by trial and ...hand, Neural ...
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FLEXIBLE SHARING IN DHT BASED P2P NETWORKS USING METADATA OF RESOURCE
... the fuzzy neural network has fuzzy decision and judgment, and has good self-learning and adaptive ability, it overcomes the disadvantages of fuzzy logic about strong subjective factors, ...
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Online Full Text
... TSK-type fuzzy network control (ATFNC) system for synchronization of a coupled nonlinear chaotic ...a neural controller and a fuzzy compensator. The neural controller uses a ...
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Fuzzy inference systems implemented on neural architectures for motor fault detection and diagnosis
... Many engineers and researchers have focused on incipient fault detection and preventive maintenance, which aim at preventing motor faults from happening [5]–[9]. Usually, devices such as fuses, overload relays, and ...
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Type-2 Fuzzy Logic Approach To Increase The Accuracy Of Software Development Effort Estimation
... type-2 fuzzy logic in which the gradient descend algorithm and the neuro- fuzzy-genetic hybrid approach have been used in order to teach the type-2 fuzzy ...
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