neuro-fuzzy system modeling
A Neuro Fuzzy System for Modeling the Depression Data
... of Fuzzy-C Means (FCM) and K-means (KM) clustering techniques were used for classifying depression grades using Beck’s Depression Inventory-II (BDI-II) ...depression, neuro-fuzzy modeling has ...
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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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Modeling and Design of Automated Industrial Process System for Regulating Temperature by using Neuro-Fuzzy system
... First of all the temperature of the liquid tank is sensed and compared with the set-point. The result or the error is then manipulated by the controller and accordingly the heater or the stirrer runs to work as per need. ...
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Quantitative Analysis of Cardiac Q Wave Modeling Using Adaptive Neuro Fuzzy Inference System
... clearly modeling the Q wave and providing a crisp output in the form a Q-wave index value which should be able to provide a comparable estimate of cardiac pathological ...
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Application of several data-driven techniques to predict a standardized precipitation index
... index modeling approach based on large-scale climate indices by using the adaptive neuro-fuzzy inference system (ANFIS), the M5P model tree and the multilayer perceptron ...
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Adaptive Neuro-Fuzzy Systems
... fact fuzzy systems are not better function approximators or classifiers than other ...of fuzzy systems: the convenient combination of local models to an overall ...a fuzzy system is the most ...
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Multioutput Adaptive Neuro-Fuzzy Inference System Based Modeling of Heated Catalytic Converter Performance
... The modeling of catalytic converter performance of the engine during cold start is a difficult ...adaptive neuro-fuzzy inference system (M-ANFIS) is used for prediction of catalyst ...
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Neuro-fuzzy-based Electronic Brake System Modeling using Real Time Vehicle Data
... Brake System (EBS) is considered as one of the most complicated systems whose performance depends on the subsystems ...mathematical modeling approach based on neuro-fuzzy network method to ...
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MODELING AND SIMULATION OF DYNAMIC VOLTAGE RESTORER (DVR) USING NEURO FUZZY INFERENCE SYSTEM
... distribution system aiming to supply reliable and high quality power to sensitive ...the modeling and analysis of DVR by comparing conventional DVR, DVR with PI controller and also DVR using Adaptive ...
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Neuro Fuzzy Modeling of Design Parameters of Connecting Rod
... the Neuro-Fuzzy modeling has received attention in the area of manufacturing processes, electrical power drive systems, electronics systems and mechanical design ...and Fuzzy Logic (FL) ...
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Modeling reservoir water release decision using adaptive neuro fuzzy inference system
... for modeling reservoir water release decision. ANFIS is a powerful modeling tool because it combines the learning ability of ANN and ...for modeling reservoir water release ...
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Modelling Metal cutting Parameters Using Intelligent Techniques
... Cutting temperature, which depends on many factors, has a significant and, mostly negative influence on cutting process parameters. On the other hand, the quality of the machined surface is one of the most important ...
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Dietary Fibers Effect from Mango Peels and Date Seeds on Rheological properties of Arabic Bread Quality: A Novel approach on applying Fuzzy Modeling in Studying Rolling/Folding and Tearing values
... and fuzzy inference system (FIS) is an effective technique for the identification and modeling of complex nonlinear ...systems. Fuzzy logic is particularly attractive due to its ability to ...
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Adaptive Neuro-Fuzzy Inference System For Rainfall-Runoff Modeling
... Neuro-fuzzy modeling refers to the way of applying various learning techniques developed in the neural network literature to fuzzy modeling or to a fuzzy inference system ...
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Modeling neuro-fuzzy system for classifyng candidates using ANFIS's
... Primjer za definiranje fuzzy skupa, uzeta su dva skupa A i B. Skup A sadržava sve brojeve veće od 100, = { | ∈ ℕ, > 100} . Skup B sadržava „puno veće“ brojeve od 100, = { | ∈ ℕ, ≫ 100} . Ova dva skupa različita ...
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Estimation of pH and MLSS using Neural Network
... adaptive neuro-fuzzy inference system (ANFIS) and feed-forward neural network (FFNN) modeling applied to the domestic plant of the Bunus regional sewage treatment ...
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An FPGA-Based Neuro-Fuzzy Sensor for Personalized Driving Assistance
... DS modeling is proposed. To perform system development, data from a subset of real-world trips of the Strategic Highway Research Program (SHRP2)’s naturalistic driving study (NDS) [30] are ...adaptive ...
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Dynamic neuro-fuzzy systems for rainfall-runoff modelling
... approaches are able to identify a direct mapping between input and output with less number of physical parameters. This study is important from hydrologic point of view as it aimed to develop rainfall-runoff model using ...
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Medical image classification and symptoms detection using neuro fuzzy
... 3. S.Y. Belal, A.F.G. Taktak, A.J. Nevill, S.A. Spencer, D. Roden, S. Bevan, “Automatic detection of distorted plethysmogram pulses in neonates and paediatric patients using an adaptive-network-based fuzzy ...
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Title: Relevance of Neural Network in Fault Detection of Single Phase Induction Motor
... Different internal motor faults (like short circuit of motor leads, interterm short circuits, ground faults, worn out bearings, broken rotor bars) along with external motor faults (e.g., phase failure, asymmetry of mains ...
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