neural fuzzy inference systems
Fuzzy inference systems implemented on neural architectures for motor fault detection and diagnosis
... monitoring systems are of particular interest because they can be used for regular analysis of machine variables and to predict possible fault conditions, so that preventive maintenance can be organized in a ...
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Performance Improvement for BLDC Motor by using Adaptive Neuro-Fuzzy Inference Systems (ANFIS)
... Neuro-Fuzzy Inference Systems (ANFIS) algorithm are considered and included to replace the conventional method of Proportional Integral and ...both neural networks and fuzzy logic ...
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Automatic Heart Disease Diagnosis System Based on Artificial Neural Network (ANN) and Adaptive Neuro Fuzzy Inference Systems (ANFIS) Approaches
... of fuzzy logic and neural networks in order to solve wide variety of real world problems in an effective ...Since neural networks are good at recognizing patterns and not good at explaining how they ...
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Comparison of ANFIS and ANN for Estimation of Thermal Conductivity Coefficients of Construction Materials
... Articial Neural Networks (ANN) and Adaptive Neuro-Fuzzy Inference Systems (ANFISs) have been used in many dierent elds, from predicting material properties to customer ...
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Highly nonlinear control of a solar thermal power plant using soft computing fuzzy tuning techniques
... supply systems. Many of these real world systems exhibit varying degrees of ...Sugeno-type fuzzy incremental controller was tuned using an ANFIS (Adaptive Neural Fuzzy Inference ...
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Neural fuzzy Inference Based Robust Adaptive Beamforming
... Array processing is an area of signal processing that has powerful tools for extracting information from signals collected using an array of sensors. The information of interest in the signal corresponds to either the ...
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Neuro fuzzy Modeling of an Eco friendly Melting Furnace Parameters using Bio fuels for the Agile Production of Quality Castings
... (TSK) fuzzy model [9]. ANFIS represents a neural network approach to the design of fuzzy inference ...the fuzzy system to learn the parameters using hybrid learning algorithm ...
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Adaptive Neuro-Fuzzy Inference System based control of six DOF robot manipulator
... The flowchart of ANFIS procedure is shown in Figure 4. AN FIS distinguishes itself from normal fuzzy logic systems by the adaptive parameters, i.e., both the premise and consequent parameters are ...
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Modeling Marshall stability of lightweight asphalt concretes fabricated using expanded clay aggregate with anfis
... and neural networks are the widely used artificial inference ...these systems has been proposed by many researchers in recent ...Neuro-Fuzzy Inference System (ANFIS) is fuzzy ...
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Modelling the formation of Ozone in the air by using Adaptive Neuro-Fuzzy Inference System (ANFIS) (Case study: city of Yazd, Iran)
... A study was conducted in 2013 on modelling and predicting the formation of ozone in the air of Mashhad city using a neural fuzzy network based on inference fuzzy-adaptive systems. It ...
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The Most General Intelligent Architectures of the Hybrid Neuro-Fuzzy Models
... Hybrid neural networks – based systems, are based on an architecture which integrates the neural networks and the fuzzy logic based system in the form of parallel ...the neural networks ...
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Multi objective reinforcement learning framework for unknown stochastic & uncertain environments
... such systems, Reinforcement Learning has proven to be a more suitable method than supervised or unsupervised learning when the systems require a selection of actions whose consequences emerge over long ...
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Predicting the Collapsibility Potential of Unsaturated Soils Using Adaptive Neural Fuzzy Inference System and Particle Swarm Optimization
... a simple indication of the system behavior. There are dierent methods for determining the primary model structure of fuzzy inference system, among which grid partition and Subtractive Clustering Method ...
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A fuzzy neural network to estimate at completion costs of construction projects Pages 477-484 Download PDF
... the neural network and it is analogous with the input vector X p = ( X p 1 , X p 2 ...the neural network’s operation is calculated through defining the cost ...the fuzzy neural model, the cost ...
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Modelling tide prediction using linear model and adaptive neuro fuzzy inference system (ANFIS) in Semarang, Indonesia
... Forecasting methods are techniques in Statistical tools for decision making. Forecasting approach for time series data can be done using two ways, the linear and non-linear approach. Forecasting methods with linear ...
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The Smith-PID Control of Three-Tank-System Based on Fuzzy Theory
... –Machine Systems and Cybernetics, 2009); Fuzzy Immune Adaptive Smith-PID Control for Water Quality Adjusting System of Thermal Power Plant (Wuhan, China, The 2nd International Workshop on Intelligent ...
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“Genetically Tuned Optimization Of Plastic Extrusion Process: A Litreture Review”
... back-propagation neural network model was used to predict the parison swells under the effect of ...2-20-20 neural network architecture with two input nodes, one hidden layer with 20 nodes, and 20 out-put ...
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An intelligent vertical handoff decision algorithm in next generation wireless networks
... as Fuzzy Logic (FL), Fuzzy Multiple Attribute Decision Making (FMADM), Neural Networks (NNs), and Genetic Algorithm, to some vertical handoff decision ...of fuzzy logic to deal with imprecise ...
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Chain Coding and Pre Processing Stages of Handwritten Character Image File
... CR systems have evolved in three stages ...early systems of automatic recognition of characters, area of concentrations are either in machine- printed text or upon small sets of well-distinguished ...
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