fuzzy inference neural network
Electricity Price Forecasting using Asymmetric Fuzzy Neural Network Systems
... Gaussian Fuzzy Inference Neural Network (AGFINN), utilizing a Takagi–Sugeno–Kang (TSK) structure, has been considered as an identification model for electricity price ...of fuzzy rules, ...
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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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Adaptive neural network fuzzy inference system for HFC processes
... The advantages of the second system consist in the repeatability and flexibility of the process, as well as in the non-linear behaviour of output data generated within the same class, due to the way in which the ...
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Forecasting of Intellectual Capital by Measuring Innovation Using Adaptive Neuro-Fuzzy Inference System
... Artificial neural networks are a group of mathematical models that imitate human brain ...common neural networks is the multilayer perceptron neural ...nonlinear neural units and ...in ...
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Calculation of Resonant Frequency for a Microstrip Antenna with Vertical Slots Using Applying Adaptive Network-Based Fuzzy Inference System
... Figure 11.below illustrates S11 curves for the whole possible situations Since the antenna resonates in more than one frequency ,it is necessary that an appropriate algorithm to detect the resonant frequencies be ...
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Computing air demand using the Takagi–Sugeno model for dam outlets
... neuro-fuzzy inference system (ANFIS) was developed using the subtractive clustering technique to study the air demand in low-level outlet ...Levenberg-Marquardt neural network (LMNN) and ...
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Forecasting Mortality Rate Using a Neural Network with Fuzzy Inference System
... Abstract. Various methods have been developed to improve mortality forecasts. The authors proposed a neuro-fuzzy model to forecast the mortality. The forecasting of mortality is curried out by an ANFIS model which ...
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Modelling tide prediction using linear model and adaptive neuro fuzzy inference system (ANFIS) in Semarang, Indonesia
... and fuzzy inference system (FIS) where neural network algorithm is used to determine FIS parameter (Chang and Lain, ...Sugeno’s fuzzy model is a sistematic approach in generating ...
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Study of Existing Work on Soft Computing Methodologies and Fusion of Neural Network and Fuzzy Logic for Estimation and Approximation
... Neuro-Fuzzy Inference System (ANFIS) and a Kernel system to solve the problem of predicting rush orders for regulating the capacity reservation mechanism in ...than Fuzzy logic for the prediction of ...
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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 ...ANFIS network makes use of a supervised learning algorithm to determine a ...
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Intelligent controllers for velocity tracking of two wheeled inverted pendulum mobile robot
... TWIP. Fuzzy Logic Control (FLC), Neural Network Inverse Model control (NN) and an Adaptive Neuro-Fuzzy Inference System (ANFIS) were designed and simulated on the TWIP ...
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Prediction of shear strength of reinforced concrete beams using adaptive neuro-fuzzy inference system and artificial neural network
... For construction of ANN models, there is no theoretical reason ever to use more than two hidden layers. For many practical problems, there is no reason to use any more than one hidden layer. Those problems that require ...
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An Adaptive Neural Network Fuzzy Inference Controller Using Predictive Evolutionary Tuning
... Many approaches have been suggested for nonlinear system control; the problem becomes more complex when uncertainties and noise are considered. One approach that has gained success when the system model is complex or ...
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International Journal of Emerging Technology and Advanced Engineering
... Propagation Neural Network (BPNN), and Dynamic Fuzzy Inference System ...propagation neural network is implemented to embed and extract the watermark in one method, while the ...
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Forecasting on Crude Palm Oil Prices Using Artificial Intelligence Approaches
... An accurate prediction of crude palm oil (CPO) prices is important especially when investors deal with ever-increasing risks and uncertainties in the future. Therefore, the applicability of the forecasting approaches in ...
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Transformer’s Load Forecasting to Find the Transformer Usage Capacity with Adaptive Neuro-Fuzzy Inference System Method
... neuro-fuzzy inference system which connects fuzzy logic system with neural network and constructs a hybrid intelligent system and benefits from the advantages of both fuzzy logic ...
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Implementation of Computational Intelligent Techniques for Diagnosis of Cancer Using Digital Signal Processor
... like Fuzzy Logic, Adoptive Neuro-Fuzzy Inference System (ANFIS) and Neural Network for diagnosis of cancer using TMS320C6713 (Texas Instruments) DSP (Digital Signal ...
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A NEURAL FUZZY APPROACH TO MODELING THE THERMAL BEHAVIOR OF POWER TRANSFORMERS
... Neuro-Fuzzy Inference System (ANFIS), Multilayer Feedforward Neural Network (MFNN) and Elman Recurrent Neural Network (ERNN) are chosen to compare with the conventional Institute ...
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Parsimonious Network Based on a Fuzzy Inference System (PANFIS) for Time Series Feature Prediction of Low Speed Slew Bearing Prognosis
... PANFIS is compared against three prominent algorithms, known as eTS [2], simp_eTS [12], and ANFIS [1]. eTS and simp_eTS are counterparts of PANFIS, which features both structural and parameter learning scenarios in the ...
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Knowledge Discovery and Diseases Prediction: A Comparative Study of Machine Learning Techniques
... (KNN), Neural Network (NN), Adaptive Network-Based Fuzzy Inference System (ANFIS), Support Vector Regression (SVR) and Classification and Regression Trees (CART) are used for diseases ...
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