cascade neural network model
A Hybrid Method for Compression of Solar Radiation Data Using Neural Networks
... used neural network models were used to predict the solar radiation data for the location “Sheep Range Black brush” in Nevada from Nevada Climate Change ...perceptron neural network (MLPNN), ...
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Cascade feed forward neural network-based model for air pollutants evaluation of single monitoring stations in urban areas
... Monitoring networks consist mainly of three stations not including monitoring station of Librino’s area insofar as the air pollution impacts from traffic congestion and related air emissions on centre of the city is very ...
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PP and PP Multi Particles Production Investigation Based on CCNN Black Box Approach
... mathematical model that can accurately describe the physical be- havior of the complex physical problem is a challenging ...Meanwhile, neural networks are a very promising tool for empirical “black-box” ...
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Cascade neural fuzzy model of analysis of short electronic unstructured text documents using expert information
... Processing), neural network, ...of neural network classifiers with methods of formalizing the text documents and representing the results of the classifier in the form of semantic ...
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Predicting creditworthiness in retail banking with limited scoring data
... regression model, and makes the assumption that the prob- ability of the dependent variable belonging to any of two differ- ent classes relies on the weight of the characteristics attached to it [1,4,5,37,41,48] ...
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Adaptive neural network cascade control system with entropy-based design
... Model-free controllers have been well developed through minimising the mean square error (MSE) performance indexes when a Gaussian distribution or others alike can be assumed for stochastic terms involved in the ...
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Parallel Cascade Correlation Neural Network Methods for 3D Facial Recognition: A Preliminary Study
... Recently, researchers tried to use General Purpose computation on Graphics Processing Units (GPGPU) as parallel programming approach. GPGPU are techniques to program GPU chips using application programming interface ...
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A New Approach for Rainfall Prediction using Artificial Neural Network
... forecasting model is very important ...Artificial Neural Network (ANN) by the Cascade-forward Back propagation Neural Network (CFBPNN) ...accuracy model to predict monthly ...
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ON THE DEVELOPMENT OF NEURAL NETWORK MODELS USING DATA MINING TOOLS
... Two neural network models ‘Multi Layered Perceptron (MLP) ‘ and ‘Cascade Correlation network ‘ have been compared and analyzed ...each model using the training data set and the ...
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A Data Mining Model by Using ANN for Predicting Real Estate Market: Comparative Study
... the neural network model by using two types of neural networks first feed forward neural network, sec- ond Cascade forward neural network, and compare to ...
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A machine learning approach to voice separation in lute tablature
... a neural network model for voice separation in lute ...This model is more flexible than the existing rule-based models in that it adapts to the data, and thus is less restricted with regard to ...
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Survey on Various Types of Noise and Methods for Noise Removal
... with neural network for new patterns should be searched (Verma and Singh ...Artificial Neural Network (ANN) comes from remarkable information processing characteristics of nonlinearity and ...
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Adaptive Cascade Classifier based Multimodal Biometric Recognition and Identification System
... probabilistic neural network (PNN) is predominantly a ...forward network with four layers as: Input layer, Pattern layer, Summation layer and Output ...
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A Neural Network Approach for Numeral Font Recognition
... An SVM in its elementary form сan be used for binary сlassifiсation. It may, however, be extended to multi сlass problems using the one-against-the-rest approaсh or by using the one-against-one approaсh. Arora and ...
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Investigating electrochemical drilling (ECD) using statistical and soft computing techniques
... computing network architecture, CANFIS with Gaussian membership function, TSK fuzzy model, and 4:9:2:1 ANN model were found to be the optimal ones, which can estimate radial overcut with ...
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Artificial Neural Network Model for Precise Estimation of Global Solar Radiation
... the neural network, Meteorological and geographical data (latitude, longitude, altitude, month, mean sunshine duration, and mean temperature) were used in the input layer of the ...Artificial neural ...
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Human-level Moving Object Recognition from Traffic Video
... Abstract. Video preserves valuable raw information. Understanding these data and then recognizing objects and tagging them are crucial to intelligent planning and decision making. Deep learning provides us an effective ...
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Argument Component Classification for Classroom Discussions
... all neural net- work models benefit from additional handcrafted features (with the exception of precision and re- call for rows 13 and ...that neural networks require a large amount of data to be trained ...
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Fast Algorithm for Modeling of Rain Events in Weather Radar Imagery
... As mentioned in the previous section, different forecasting techniques can be used to track the network parameters. Some of these methods were also discussed in the previous work [3]. More specifically, for the ...
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Neuro-Fuzzy Scheduler for the Control of Real Time Spherical Tank Process
... general neural- network model for fuzzy logic control and decision ...connectionist model combined the idea of fuzzy logic controller and neural network structure and learning ...
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