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Neural Networks and Artificial Intelligence

Advanced Applications Of Neural Networks And Artificial Intelligence: A Review

Advanced Applications Of Neural Networks And Artificial Intelligence: A Review

... Abstract— Artificial Neural Network is a branch of Artificial intelligence and it has been accepted as a new computing technology in computer science ...of Artificial ...

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Artificial Intelligence for Speech Recognition Based on Neural Networks

Artificial Intelligence for Speech Recognition Based on Neural Networks

... in neural network theory had been built and tested in the first study of the neurological computer in the 1950s, where the application contacts automatically and during this stage the term preceptor called the ...

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Artificial Intelligence Technique for Speech Recognition Based on Neural Networks

Artificial Intelligence Technique for Speech Recognition Based on Neural Networks

... Neural network estimation was carried out as follows. There have been several runs of the system (here are the results for 20 runs). In each run was chosen as the test case with the worst result and calculated ...

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Artificial Intelligence Neural Networks Applications in Forecasting Financial Markets and Stock Prices

Artificial Intelligence Neural Networks Applications in Forecasting Financial Markets and Stock Prices

... In their study (Chen, Leung, Daouk, 2003) the authors attempt to model and predict the direction of market index of the Taiwan Stock Exchange, one of the fastest growing financial exchanges in the developing Asian ...

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Artificial neural networks as models of stimulus control

Artificial neural networks as models of stimulus control

... Artificial neural networks represent an important advance in the modelling of ner- vous systems and behaviour (see ...years artificial neural networks have been actively ...

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A Review on Ensemble of Diverse Artificial Neural Networks

A Review on Ensemble of Diverse Artificial Neural Networks

... Data mining (sometimes called data or knowledge discovery) is the process of analyzing data from different perspectives and summarizing it into useful information - information that can be used to increase revenue, cuts ...

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INTRODUCTION TO ARTIFICIAL NEURAL NETWORKS

INTRODUCTION TO ARTIFICIAL NEURAL NETWORKS

... the artificial neural network application in processing ...An artificial neural network as a computing system is made up of a number of simple and highly interconnected processing elements, ...

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Artificial neural networks in freight rate forecasting

Artificial neural networks in freight rate forecasting

... and artificial intelligence methods (Yu et ...hand, artificial intelligence (AI) techniques, such as ANNs, genetic algorithms (GA) and fuzzy time series (FTS), with their strong self-learning ...

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Image Processing Using Artificial Networks and Neural Networks

Image Processing Using Artificial Networks and Neural Networks

... This artificial intelligence makes use of human skills in a more efficient manner than the conventional mathematical models ...three-layer neural network using backpropagation algorithm becomes a ...

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From Artificial Intelligence to Artificial Art: Deep Learning with Generative Adversarial Networks

From Artificial Intelligence to Artificial Art: Deep Learning with Generative Adversarial Networks

... From 2012 onwards, Google researchers efforts have been completely revolutionized the state of art of Deep Learning. The term “deep” refers to the number of levels, or layers, that characterizes the depth of the ...

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Superintelligent Deep Learning Artificial Neural Networks

Superintelligent Deep Learning Artificial Neural Networks

... Learning Artificial Neural ...A neural network consists of many interconnected ...human intelligence is called Machine Learning. Deep Learning Artificial Neural Networks ...

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Medical imaging analysis with artificial neural networks

Medical imaging analysis with artificial neural networks

... that neural networks have been widely reported in the research community of medical imaging, we provide a focused literature survey on recent neural network developments in computer- aided diagnosis, ...

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A. Artificial Neural Networks

A. Artificial Neural Networks

... enhance artificial neural networks methods to support the prediction in stock market ...computational intelligence approaches designed to solve financial market ...a neural network ...

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Virus Detection using Artificial Neural Networks

Virus Detection using Artificial Neural Networks

... an artificial neural network with the inputs from Portable Executable (PE) Structure of executable files, as they learn from the training data and will be able to identify unknown virus ...the neural ...

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An Evolutionary Approach: Analysis of Artificial Neural Networks

An Evolutionary Approach: Analysis of Artificial Neural Networks

... real neural networks, and study behavior and control in animals and machines, but also there are ANN models which are used for engineering purposes, such as pattern recognition, forecasting, and data ...

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Nowcasting US GDP with artificial neural networks

Nowcasting US GDP with artificial neural networks

... recurrent neural networks, elastic nets and super learners to forecast GDP growth of seven major advanced and developing ...recurrent neural networks to daily data of several ...

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Traction control using artificial neural networks

Traction control using artificial neural networks

... .16: Lateral acceleration GRNN prediction error — course 1 Absolute Error for Straight Line Course - Lateral Acceleration without noise - GRNN with 40 Nodes, Sigma = 0.2... 7: Yaw angle [r] ...

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Face Recognition using Artificial Neural Networks

Face Recognition using Artificial Neural Networks

... Forward sweep defines the network from the input layer to the output layer, in which it propagates the input vectors through the network to provide outputs at the output layer in the end. During the forward sweep, the ...

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Forecasting time series with artificial neural networks

Forecasting time series with artificial neural networks

... small networks over large networks (7-10% lower error than with baseline ...large networks for forecasting long horizon based on long history had 20-25% higher error than SARIMA ...

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Time Series Classification with Artificial Neural Networks

Time Series Classification with Artificial Neural Networks

... Backpropagation through time, discussed above, has a limitation called the vanishing gradient problem. Figure 1.8 pictures the sigmoid function and its derivative. It can be seen that the limits of the derivative ...

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