Generalized Regression Neural Network
The Research of Tax Inspection Based on Generalized Regression Neural Network
... the generalized regression neural network (in short: GRNN) to assist tax inspection case ...of generalized regression neural network and applies it in the tax ...
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Evaluation of food logistics system based on generalized regression neural network
... with generalized regression neural ...the generalized regression neural network evaluation model more accurate; 2) optimize the study of generalized ...
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Structural Elucidation of Guaiane Sesquiterpenes from 13C Data using Generalized Regression Neural Network (GRNN) and Scatter Plots Methods
... Generalized Regression Neural Network and Scatter Plots methods have proved to be useful in the elucidation of structures of Guaiane-type ...
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Fingerprint Recognition Using Markov Chain and Kernel Smoothing Technique with Generalized Regression Neural Network and Adaptive Resonance Theory with Mapping
... divergent neural networks, consisting Generalized Regression Neural Network (GRNN) and Adaptive Resonance Theory with mapping ...
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Using a Generalized Regression Neural Network Prediction Tool to Estimate Thermal Performance in A Heat Exchanger By using Triple Elliptical Leaf Angle Strips with Opposite Orientation and Same Direction
... In this investigation statistical tool of generalized regression neural network is used which is an application of artificial neural network. Using GRNN various outputs can be ...
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Stator Turn-to-Turn Fault Detection of Induction Motor by Non-Invasive Method Using Generalized Regression Neural Network
... Artificial neural network (ANN) methods are robust and less model dependent for fault diagnosis when the fault signature can be directly achieved using the sampling ...Therefore, generalized ...
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Fingerprint Classification Using Kernel Smoothing Technique and Generalized Regression Neural Network and Probabilistic Neural Network
... Artificial Neural Network (ANN) is another popular method used for classification ...including Generalized Regression Neural Network (GRNN) and Probabilistic Neural ...
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Generalized Regression Neural Network Based on Soft Sensor for Multicomponent Distillation Column
... In this study, trial and error approach was used to determine the optimum topology of the network. Starting from minimum number of neuron, the number of neurons in the hidden layer was increased upto 15 neurons in ...
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THE NOVEL METHOD FOR RECOGNITION OF AMERICAN SIGN LANGUAGE WITH RING PROJECTION AND DISCRETE WAVELET TRANSFORM
... Sign Language is a language that allows individuals with hearing or speech impairment to communicate with themselves and their surroundings and has the feature of not being a universal language. This language, which is ...
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Disease Identification in Cotton Plants Using Spatial FCM & PNN Classifier
... multiple regression, artificial neural network (back propagation neural network, generalized regression neural network) and support vector machine (SVM) was ...
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A hybrid seasonal prediction model for tuberculosis incidence in China
... artificial neural network was a model which was broadly applied in multivariate nonlinear analysis recently [14] and could be a supplement of linear ...and generalized regression neural ...
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Estimation of Punching Shear Capacity of Concrete Slabs Using Data Mining Techniques
... 2. 1. Generalized Regression Neural Network (GRNN) The GRNN was proposed by Specht [36], to perform linear and non-linear regressions. The GRNN structure contains four layers: the input units ...
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A Unique Approach to Epilepsy Classification from EEG Signals Using Dimensionality Reduction and Neural Networks
... the Neural Networks (NN) such as Cascaded Feed Forward Neural Network (CFFNN), Time Delay Neural Network (TDNN) and Generalized Regression Neural Network ...
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A Radial Basis Function Approach to Retrieve Soil Moisture and Crop Variables from X-Band Scatterometer Observations
... the network until the sum squared error falls beneath an error goal or a maximum number of neurons are ...A generalized regression neural network (GRNN) is a specialized one for ...
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Suspended Sediment Simulation using Ann based Generalized Feed Forward Neural Network (GFF) and Multi Linear Regression Method (MLR)
... spectrum of water resources engineering problems. The nonlinear nature of suspended sediment load series necessitates the utilization of nonlinear methods for simulating the suspended sediment load. In this study ...
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Comparison of Artificial Intelligence Techniques for river flow forecasting
... Artificial Neural Network (ANN) methods, Generalized Regression Neural Networks (GRNN) and Feed Forward Neural Networks (FFNN), and Auto-Regressive (AR) models for forecasting of ...
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Artificial neural network, genetic algorithm, and logistic regression applications for predicting renal colic in emergency settings
... Table 2 shows the overall performances of each model. Figure 2 depicts the comparison of ANN and logistic regression applications after the ROC analysis according to the prediction rates. The AUC for GA rules may ...
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Study The Relationship Between Emotional Intelligence Of The Managers And Their Entrepreneurial Personality In Air-Handling Units And Industrial Diffusers Manufacturers With Using Artificial Neural Network
... artificial neural network based on some simple neurons has been established that the neurons in layers by weights and activation functions are organized and linked ...A neural network is ...
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Support Vector Regression Integrated with Fruit Fly Optimization Algorithm for River Flow Forecasting in Lake Urmia Basin
... Monthly river flow forecasting using artificial neural network and support vector regression models. 316[r] ...
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A generalized ABFT technique using a fault tolerant neural network
... of neural networks is not suitably utilized by current common learning algorithms such as BP, in order to have or enhance fault tolerance in neural ...of neural network can be greatly improved ...
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