adaptive neural network method
Deep Learning in an Adaptive Function Neural Network
... Along the lines of the previous section, it is apparent that the learned functions are very well-regulated. It is possible, for a given set of analytical function prototypes to determine which analytical function matches ...
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Transformer’s Load Forecasting to Find the Transformer Usage Capacity with Adaptive Neuro-Fuzzy Inference System Method
... ANFIS method has all the advantages possessed by fuzzy inference system and artificial neural network ...ANFIS method it is expected that the time required to forecast the electrical load can ...
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A Direct Adaptive MNN Control Method for Stage Having Paired Reluctance Linear Actuator with Hysteresis
... control method is proposed for the stage having paired reluctance linear actuator with hysteresis using the direct adaptive neural network, which is used as a learning machine of ...this ...
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Duct Modeling Using the Generalized RBF Neural Network for Active Cancellation of Variable Frequency Narrow Band Noise
... passive method, it is possible using the active method to suppress or reduce the noise in a small space particularly in low frequen- cies (below 500 Hz) [1, ...control method by pro- ducing a sound ...
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Adaptive Neural Network Tracking Control for a Class of SISO Affine Nonlinear Uncertain Systems
... direct adaptive neural network tracking control scheme is presented for a class of SISO affine nonlinear uncertain ...in neural networks are updated using a gradient descent method ...
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Real-time feature extraction of P300 component using adaptive nonlinear principal component analysis
... extraction method for P300 components using an adaptive nonlinear principal component analy- sis (ANPCA) incorporating the multilayer neural network (MNN) is ...and neural sciences ...
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Estimation of Punching Shear Capacity of Concrete Slabs Using Data Mining Techniques
... simpler method to compete with the simplicit y of empirical formula can be use of data mining ...Artificial Neural Network (ANN), with few studies on use of Adaptive Neuro-fuzzy Inference ...
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Detecting central fixation by means of artificial neural networks in a pediatric vision screener using retinal birefringence scanning
... the neural network was created, trained, validated, and tested on the calibration data, in a further step, it was tested on our data set of clinical data (described in detail above under the “Data” ...
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Neural Network and Adaptive Feature Extraction Technique for Pattern Recognition
... self-organizing neural networks and the statistical method of principal component ...2-layer network with i inputs and j outputs (with i > j) can be used to extract the first j principal ...
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Estimation of harmonics using adaptive wavelet neural network
... an adaptive wavelet neural network (AWNN) is the most appropriate for prevailing low-order harmonics ...the network parameters which is a easy, fast converging and reliable learning ...
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Adaptive Control of a DC Motor Using Neural Network Sliding Mode Control
... In this paper a DC motor is controlled via the input voltage. The control design and theory for controlling a DC motor via current is nearly the same. For simplicity, a constant value as a reference signal is injected to ...
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GROUP OF RECURRENT NEURAL NETWORKS
... this method are firstly, visual inspection of the obtained sources is still needed in order to perform artifact rejection and secondly, there is unwanted data loss in the cases where the entire trials are ...
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Lyapunov Based Dynamic Neural Network for Adaptive Control of Complex Systems
... Artificial Neural Network (ANN) learning and generali- zation capabilities to achieve accurate speed tracking and ...direct method unlike many computa- tional intelligence- Based ...
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Quality Inspection and Grading of Agricultural and Food Products by Computer Vision a Review
... The relationship between colour and texture features of wheat samples to scab infection rate was studied using a neural network method [63]. It was found that the infection rates estimated by the ...
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Fuzzy inference systems implemented on neural architectures for motor fault detection and diagnosis
... hybrid neural/fuzzy system is a fairly new concept in the motor fault detection ...hybrid neural/fuzzy fault detector is used to solve the motor fault detection ...the neural/fuzzy fault detector is ...
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Modelling and predicting of MODIS leaf area index time series based on a hybrid SARIMA and BP neural network method
... linear method or nonlinear method. In this paper, SARIMA, BP neural network and a hybrid method of SARIMA-BP neural network were used for modeling and predicting MODIS LAI ...
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PID Neural Network Motor Synchronization Control Based on the Improved PSO Algorithm
... simplified adaptive mutation PSO - PIDNN algorithm enables the system axis 1 and 2 output without overshoot phenomenon, and can quickly reach the stable state, has good quickness and adaptability, meets the ...
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Prediction of Heart Disease using RNN Algorithm
... authors applied ANN on two distinctive breast malignancy dataset. Both of these datasets utilizes the morph metric attributes. An enhanced ANN model [30] has been utilized. Back propagation has been utilized to prepare ...
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Stable Adaptive Neural Control of a Robot Arm
... stable adaptive control scheme based on the use of recurrent neural ...the method for engineers, the application and valida- tion of IDNC have been applied to robot manipulator which is a nonlinear ...
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Comparison of Artificial Intelligence Techniques for river flow forecasting
... were selected by trial and error method during the training process. On the other hand, as can be seen in Fig. 10, the val- ues of the E and CORR of R-I M2 GRNN model for Seyhan River are higher than those of ...
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