present neural network approach
A Neural Network Approach to Selectional Preference Acquisition
... a neural network’s param- eters requires a large amount of training ...authors present a method for training a neural network language model from un- labeled data by corrupting actual attested ...
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Inversion of Schlumberger resistivity sounding data from the critically dynamic Koyna region using the Hybrid Monte Carlo-based neural network approach
... the present work, we developed a Bayesian neural network approach via a powerful Hybrid Monte Carlo ap- proach (Bishop, 1995; Nabney, 2004; Maiti and Tiwari, 2009, 2010a) for estimating true ...
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A Neural Network Approach for ECG Classification
... The ECG is a bioelectric signal, which records the heart‟s electrical activity versus time; therefore it is an important diagnostic tool for assessing heart function. The electrical current due to the depolarization of ...
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Analytical and numerical solution of differential equations with generalized fuzzy derivative
... to present a novel approach based on the fuzzy neural network for finding the numerical solution of the first order fuzzy differential equations under generalized ...feed-forward neural ...
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Neural Networks using Genetic Algorithms
... artificial neural network/genetic algorithm approach to on-line switching operations for the optimization of electrical power systems” had intended to present an approach to decision ...
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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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Modular Neural Network Approach for Data Classification
... Modular Neural Network as a modelling tool for data ...we present a MNN architecture for supervised ...forward neural network with back propagation ...
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Chain Based RNN for Relation Classification
... We present a novel approach for relation clas- sification, using a recursive neural network (RNN), based on the shortest path between two entities in a dependency ...lower network, ...
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An Artificial Neural Network Modelling Approach for Development of QSAR Model for Anticancer Activity of Gossypol Acetic Acid against Anticancer Target BCL2
... ANN analysis is performed on all the compounds using R software; we have included all 70 molecules of the training set for the model generation. A number of suitable models are developed by using these 70 molecules ...
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A Survey of Image Segmentation Methods using Conventional and Soft Computing Techniques for Color Images
... to present a survey of various approaches for color image segmentation ...novel approach for color image segmentation using soft computing ...based approach, Genetic algorithm based approach ...
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A Novel Hybrid Technique Based upon Static and Dynamic Clustering to Reduce Consumption in Wireless Sensor Network
... the network and network performance ...using neural network approach. In neural networks weights can be adjusts easily by applying some ...is present in a cluster and ...
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SpaceRefNet: a neural approach to spatial reference resolution in a real city environment
... We present a neural network-based approach for identifying pedestrian’s references (using a network called RefNet) and resolving them to appropriate geo- graphic objects (using a ...
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APPLICATION OF MULTILAYER PERCEPTRON BASED ARTIFICIAL NEURAL NETWORK FOR MODELING OF RAINFALL RUNOFF IN A HIMALAYAN WATERSHED
... ANN approach over traditional methods ...artificial neural network (ANN) models, multi layer feed-forward neural network using Levenberg–Marquardt learning algorithm (LMFF) and radial ...
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Neural Network Toolbox for MATLAB - Free Computer, Programming, Mathematics, Technical Books, Lecture Notes and Tutorials
... Perceptron networks have several limitations. First, the output values of a perceptron can take on only one of two values (0 or 1) due to the hard-limit transfer function. Second, perceptrons can only classify linearly ...
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A New Method for Intrusion Detection Using Genetic Algorithm and Neural network
... the network and its ability to exploit the best ...the neural network. Then, through a dynamic neural network, our network can be carefully chosen to determine the optimal ...
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Osmotic Drying Rate Estimation for Dehydration of Beetroot Slices using Artificial Neural Network
... the present work is to study the effect of concentration of sodium chloride & temperature of the osmotic solution on the osmotic dehydration of beetroot ...Artificial Neural network models for ...
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Using Feature Weights to Improve Performance of Neural Networks
... performed approach of incorporating feature importance into neural network ...good approach, however Expert knowledge is available in some domains or correlation of same features could be ...
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MindLab Neural Network Approach at BioASQ 6B
... Convolutional neural networks (CNN) are a popu- lar method for image analysis thanks to their abil- ity to capture spatial invariant patterns. In the pro- posed method, they play a similar role, but in- stead of ...
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Application of Multiagent Systems to Three-Dimensional Positioning Problem in Indoor Environments Based on IEEE 802.11
... hybrid approach to resolving this problem is proposed through the development of a multiagent system composed of a Bayesian network and a deep neural network for 3D indoor ...proposed ...
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Short Term Load Forecasting With Feed Forward Neural Network Algorithm
... Similar-day approach, Regression methods and expert ...forward neural network algorithm to forecast future half hourly load demand for 24 hours or one week ahead with minimum ...
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