fuzzy inference neural networks
Short Term Electricity Price Forecasting Using a Combination of Neural Networks and Fuzzy Inference
... artificial neural network, ANN, based approach for estimating short-term wholesale electricity prices using past price and demand ...a fuzzy inference technique is em- ployed to handle data that lies ...
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Improving the Efficiency of Forest Cover Forecasting using ANFIS
... regression neural networks, fuzzy inference systems, machine learning techniques and ...the neural networks are considered to be the defacto standard for trend analysis, and are ...
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Neural fuzzy Inference Based Robust Adaptive Beamforming
... The neural networks try to shape the biological functions of the human ...first Neural Network model and ...the neural networks is the fact that these structures can learn with examples ...
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Calculation of Resonant Frequency for a Microstrip Antenna with Vertical Slots Using Applying Adaptive Network-Based Fuzzy Inference System
... network-based fuzzy inference system (ANFIS) for analysis of the resonant frequency of a microstrip rectangular patch antenna with two equal size slots which are placed on the patch ...artificial ...
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Virtual Sensors for Safe Operation of Electrolyser and Hydrogen powered Car
... Artificial Neural Networks (ANNs) and Adaptive Neuro-Fuzzy Inference System (ANFIS) are presented as virtual sensors for the accurate estimation of hydrogen parameters such as the percentage ...
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Fuzzy inference systems implemented on neural architectures for motor fault detection and diagnosis
... of fuzzy logic and neural networks, a better understanding of the heuristics underlying the motor fault de- tection/diagnosis process and successful fault detection/diagnosis schemes can be ...two ...
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Oil Forecasting Using Artificial Intelligence
... belief networks, (DBNs) have been presented for the first time by Hin- ton et ...of neural networks (NN) and Fuzzy Inference Systems (FIS) in terms of improving the accuracy of ...
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Control of Non Linear Two Mass Drive System using ANFIS
... artificial neural network that is based on Sugeno fuzzy inference ...of fuzzy logic and neural networks by clustering values in fuzzy ...both neural networks ...
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“Genetically Tuned Optimization Of Plastic Extrusion Process: A Litreture Review”
... artificial neural networks (ANN), fuzzy logic, genetic algorithms (GA),Adaptive Neuro fuzzy inference system (ANFIS), ANFIS+GA and their response surface methodology are ...
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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 ...
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Comparison of Artificial Intelligence Techniques for river flow forecasting
... Neuro Fuzzy Inference Sys- tem (ANFIS) and Artificial Neural Network (ANN) methods, Generalized Regression Neural Networks (GRNN) and Feed Forward Neural Networks (FFNN), ...
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Study of Existing Work on Soft Computing Methodologies and Fusion of Neural Network and Fuzzy Logic for Estimation and Approximation
... house-building. Fuzzy logic systems, considering the city plans, the nearness to cultural, medical, training and educational buildings, the public transportations systems, the other environmental factors and the ...
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The Smith-PID Control of Three-Tank-System Based on Fuzzy Theory
... 2009); Fuzzy Immune Adaptive Smith-PID Control for Water Quality Adjusting System of Thermal Power Plant (Wuhan, China, The 2nd International Workshop on Intelligent Systems and Applications (ISA2010), 2010); The ...
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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 was ...
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Deduction of reservoir operating rules for application in global hydrological models
... Adding more membership functions or input variables to the configuration of the network increases the number of fuzzy rules. It is clear that increasing the time range over which Q and S are considered improves ...
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Vol 6, No 6 (2015)
... solving fuzzy differential equations. In this proposed method, fuzzy neural network model (F NN M) is applied as universal ...use fuzzy trial function; this fuzzy trial function is a ...
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Highly nonlinear control of a solar thermal power plant using soft computing fuzzy tuning techniques
... Mamdani-type fuzzy incremental controller (Loebis, 2000), which due to its simplicity, and use over the whole operating range of the plant, required a relatively large number of fuzzy sets, membership ...
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Soft-Computing Based Data Mining: A Review
... (involving fuzzy sets, neural networks, genetic algorithms, and rough sets) are most widely applied in the data mining step of the overall KDD ...process. Fuzzy sets provide a natural ...
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Implementation of Computational Intelligent Techniques for Diagnosis of Cancer Using Digital Signal Processor
... interconnected neural computing elements that have the ability to learn and thereby acquire knowledge and make it available for use ...[17]. Neural networks are applicable in virtually every ...
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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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