artificial neural network
Estimation of Proper Strain Rate in the CRSC Test Using a Artificial Neural Networks
... DESIGN ARTIFICIAL NEURAL NETWORK MODEL Neural networks are computer models that mimic the knowledge acquisition and organization skills of the human brain. Since, the characteristics of a neural ... GW (1992). " ;Neural network modeling of the mechanical behavior of sand," Proc. 9th Conf. ASCE, New York, pp 421-424. Garson, GD (1991). "Interpreting neural- network connection ... In this study, a back-propagation neural network model for estimating of proper strain rate form soil parameter is proposed. The back-propagation neural network program adopted in the present...
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ARTIFICIAL NEURAL NETWORKS – ARCHITECTURES AND APPLICATIONS doc
... of Neural Networks 163Hazem M. El-BakryChapter 9 Applying Artificial Neural Network Hadron - HadronCollisions at LHC 183Amr Radi and Samy K. HindawiChapter 10 Applications of Artificial Neural ... distribution. Artificial Neural Networks – Architectures and Applications6Biologically Plausible Artificial Neural Networks 13Figure 10. Representation of (b) KI and (c) KII sets by networks of ... entities, such as roads and optical fibers. This type of network is calleda “geographic network or spatial network. Neural networks are spatial networks [56].From a computational perspective, two...
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Artificial Neural Networks - a Useful Tool in Air Pollution and Meteorological Modelling pdf
... Conclusion Two types of artificial neural networks were shown to be useful tools for environmental modelling: the multilayer perceptron neural network MPNN and the Kohonen neural network KNN. MPNN ... of artificial neural networks that can cover a huge variety of air pollution and meteorological modelling applications. The two selected are the Multilayer Perceptron artificial Neural Network ... www.intechopen.com Advanced Air Pollution 496 2. Artificial neural networks – several types for different purposes Artificial neural networks can be divided into several groups according...
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vehicle signal analysis using artificial neural networks
... -0.18 5.26 93.9 B(10) 13 10.6 98.0 5. Conclusions In this study, the applicability of artificial neural networks (ANN) is investigated for the improvement of conventional B-WIM systems so that ... however the accuracy decreased for individual axle weights [10]. The application of artificial neural networks (ANN) to the B-WIM was attempted in 2003 by Gonzalez et al. for noise removal ... ISSN 1424-8220 www.mdpi.com/journal/sensors Article Vehicle Signal Analysis Using Artificial Neural Networks for a Bridge Weigh-in-Motion System Sungkon Kim 1, Jungwhee Lee 2,*, Min-Seok...
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a facial expression classification system integrating canny, principal component analysis and artificial neural network
... USING ARTIFICIAL NEURAL NETWORK In this paper, we use Multi Layer Perceptron (MLP) Neural Network with back propagation learning algorithm. A. Multi layer Perceptron (MLP) Neural Network ... with Rapid Facial Expression Classification Using Artificial Neural Network [10], Facial Expression Classification Using Multi Artificial Neural Network [11] in the same JAFFE database. TABLE ... Facial Expression Classification Using Artificial Neural Networks [10] 73.3% Facial Expression Classification Using Multi Artificial Neural Network [11] 83.0% Proposal System...
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a new type of structured artificial neural networks
... butcoexisting processes: (1) new information arrives as theA new type of Structured Artificial Neural Networksbased on the Matrix Model of ComputationSergio PissanetzkyResearch Scientist. Memb ... version of SCA, discuss the advantages ofMMC ANNs, and illustrate with a small example.Keywords: neural networks, dynamic systems, ontologies,self-organizing systems, artificial intelligence, semantic ... consider the MMC as a structured,massively parallel, ge neralized, self-organizing, artificial neural network. In Section 2 we define the MMC, in-troduce terminology, discuss the hierarchical organiza-tion...
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audio to visual speech synthesis using artificial neural networks
... speechmovements by training an artificial neural network to associate or map fundamental acousticproperties of auditory speech to our visible speechparameters. Neural networks have been shown tobe ... indicator of network performance. The networks varied somewhat intheir abilities to reproduce the output parametersof each speaker (0.75 to 0.84 mean correlationacross all parameters).Each network ... in such a way that all parameters variedbetween 0.05 and 0.95.We used a feed-forward artificial neural network (ANN) with three layers, as shown in Figure 2.The acoustic input is streamed at...
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facial expression classification based on multi artificial neural network
... many Neural Networks together, so we call it Multi Artificial Neural Network (MANN). 3 Multi Artificial Neural Network apply for image classification 3.1 The proposal MANN model Multi Artificial ... any in L given classes, the Artificial Neural Network identify and report results to the outside given classes. In this paper, we propose the Multi Artificial Neural Network (MANN) model to apply ... into responsive class using a Neural Network called Sub Neural Network (SNN) of MANN. Lastly, we use MANN’s global frame (GF) consisting some Component Neural Network (CNN) to compose the classified...
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backpropagation artificial neural network in c++ - codeproject
... and 1.0. Neural Network ClassesThe neural network is composed from the following classes:ANNetworkANNLayerANeuronANLinkThe ANNetwork class contains the implementation of the neural network ... layer:ANNetwork::ANNetwork(const wchar_t *fname);ANNetwork::ANNetwork(int layers_number, int *neurons_per_layer);int nerons_per_layer[4] = {128, 64, 32, 10};ANNetwork *ann = new ANNetwork(4, ... plr->neurons[n]; Articles » General Programming » Algorithms & Recipes » Neural NetworksBackpropagation Artificial Neural Network in C++By Chesnokov Yuriy, 20 May 2008Download demo - 95.7 KBDownload...
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báo cáo hóa học: " Error mapping controller: a closed loop neuroprosthesis controlled by artificial neural networks" doc
... with a non-linearblack-box model, such as an artificial neural network (ANNs). Chang et al. [16] proposed a NEUROPID con-troller composed by a neural network trained to behave asinverse model ... Narendra K, Parthasarathy K: Identification and con-trol of dynamical systems using neural networks. IEEE Trans Neural Networks 1990, 1:4-27.23. Matsuoka K: Noise injection into inputs in back-propagationlearning. ... H: Neural network control of functional neu-romuscular stimulation systems: Computer simulation stud-ies. IEEE Trans Biomed Eng 1995, 42(11):1117-1127.18. Riess J, Abbas J: Adaptive neural network...
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Artificial Neural Networks Industrial and Control Engineering Applications Part 1 pdf
... quality index using a feed-forward back-propagation network in an artificial neural network system / 14 Artificial Neural Network- embedded Expert System for the Design of Canopy ... m/min because of the ARTIFICIAL NEURAL NETWORKS ͳ INDUSTRIAL AND CONTROL ENGINEERING APPLICATIONSEdited by Kenji SuzukiReview of Application of Artificial Neural Networks in Textiles ... orders@intechweb.org Artificial Neural Networks - Industrial and Control Engineering Applications, Edited by Kenji Suzuki p. cm. ISBN 978-953-307-220-31 Review of Application of Artificial Neural Networks...
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Artificial Neural Networks Industrial and Control Engineering Applications Part 2 doc
... the RBF network was applied in fabric defect classification Artificial Neural Network Prosperities in Textile Applications 51 test the generalization ability of the trained neural network. ... of data are available Artificial Neural Networks - Industrial and Control Engineering Applications 44 Semnani & Vadood, 2009 applied the artificial neural network (ANN) to predict ... zero mean and Artificial Neural Network Prosperities in Textile Applications 53 properties are surface tension and viscosity which are modeled using two artificial neural networks (ANNs)...
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Artificial Neural Networks Industrial and Control Engineering Applications Part 3 doc
... effect of number of hidden layer in neural network model. The highest correlation has been found in artificial neural network with three hidden layers. The neural network model with three hidden ... been predicted accurately using artificial neural network. Empirical models have also been developed for the tensile properties and found that artificial neural network models are more accurate ... Modelling of Needle-Punched Nonwoven Fabric Properties Using Artificial Neural Network 77 Empirical Model Artificial neural network models Fabric code Exp AP Pre AP AE, %1 HL Pre...
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Artificial Neural Networks Industrial and Control Engineering Applications Part 4 pot
... Depending on the structure of a neural network designed for use in a certain problem, two general neural networks can be designed, namely feedback and feedforward neural networks. The most widely ... ,njijijizWxbj p==+=∑ (1) Fig. 1. A schematic description of artificial neural network configuration Artificial Neural Networks - Industrial and Control Engineering Applications 120 ... spectroscopy using artificial neural networks, Journal of the European Optical Society – Rapid Publications, Vol. 3, (March 2008) 08011, ISSN: 19902573 Application of Artificial Neural Networks in...
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