model-based neural networks
A Simple Scalable Neural Networks based Model for Geolocation Prediction in Twitter
... efficient model. Our model is a variant of Joulin et ...fastText model is simple, the accuracy of fastText is on par with deep complex models on several ...fastText model trains much faster ...
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Artificial Intelligence Applied to Project Success: A Literature Review
... a model that permits us to predict this cost and Schedule increments based on data collected from 62 industrial projects and 78 construction ...first based on a statistical approach, and the second ...
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Neural Utterance Ranking Model for Conversational Dialogue Systems
... NUR model for conversa- tional dialogue systems. Our model ranks candi- date utterances by their suitability in given con- texts using neural ...proposed model encodes utterances in context ...
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Mathematical model for the evaluation of risk of emergency situations at a dangerous technical object based on artificial neural networks
... hypothetical model in relation to ...2], based on the theory of ...[3], based on the software-hardware complex; the application of mathematical analysis in ...artificial neural ...
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CONVOLUTION NEURAL NETWORK (CNN) BASED OBJECT DETECTION IN OCEANOGRAPHIC IMAGERY
... proposed model has been designed by using the neural networks with the color and texture based features for the detection and analysis of the objects in the oceanographic ...
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Multivariate synthetic streamflow generation using a hybrid model based on artificial neural networks
... A model for multivariate streamflow generation is presented, based on a multilayer feedforward neural ...the model results from two components, the neural network (NN) deterministic ...
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Method of Wireless Sensor Network Data Fusion
... brain, neural network has powerful parallel pro- cessing ability ...computer networks, the most commonly used are BP neural networks and RBF neural networks, and an improved ...
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Dynamic visual cryptography with Arnolds logarithm using ANN for medical data protection
... Artificial neural networks (ANNs) have been tested to solve many ...A Neural Network is a appliance that is perform to model the way in which the brain performs a work or function of ...
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Rumor Classification Model Based on Deep Convolutional Neural Networks
... Convolutional Neural Network (CNN) is developed on the basis of the standard neural network, are as for neural network on the overall architecture is very similar, both by the neuron as a node and ...
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Research on Classification of Surface Defects of Hot rolled Steel Strip Based on Deep Learning
... classification based on deep learning is proposed. Based on the Convolutional Neural Networks model and the surface defect data set of Northeast University, the proposed method is ...
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Kalman Filters versus Neural Networks in Battery State of Charge Estimation: A Comparative Study
... On the other hand, there are several indirect methods that are used to estimate the SOC. Those methods can be very accurate and reliable in general. Among those methods are extended Kalman filter (EKF) and artificial ...
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Novel Radial Basis Function Neural Networks based on Probabilistic Evolutionary and Gaussian Mixture Model for Satellites Optimum Selection
... GA based RBFNN ' & " ! : !6 ! !5% ! " ! ' " ! " CP ! ! " ! !! 6" " ! " ! P? 6" ! ! " " ! '! ? "! !L%=EL ': ! QPP QPP # ! ! 5 ! : ? ! ! //: !$%6! 5 " $ %6 ! ...
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A SYSTEMATIC REVIEW OF MOBILE BASED ASSESSMENT ACCEPTANCE STUDIES FROM 2009 TO 2019
... with neural networks to produce a hybrid neuro-fuzzy model that can help in curtailing the risk of ...hypertension. Neural networks are a well-known classification schemes that builds ...
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JTML at SemEval 2019 Task 6: Offensive Tweets Identification using Convolutional Neural Networks
... a neural model based on Convolutional Neural Networks to identify and categorize offensive tweets on social ...The model outperforms baseline models and other Se- quential Models ...
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An agent based method for predicting monthly maximum & minimum quote prices
... our model, each particle is an Elman neural network initiated with some random weight and bias ...Elman networks. At this time the Elman networks are properly learned with the training data ...
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A Dependency Based Neural Network for Relation Classification
... to model the ADP structure in a neural network ...two neural networks are used to model shortest dependency paths and dependency subtrees ...convolutional neural network (CNN) is ...
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Novel Approaches on Sovereign Credit Ratings
... The model aims to classify the countries as investable or speculative with the Artificial Neural Networks method based on the sovereign credit ratings of the CRAs in terms of short term ...
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... artificial neural networks to the prediction of the mechanical behaviour of concrete materials at high ...artificial neural network (ANN) based model, to predict the confined ...
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The Application of Neural Network in Multiple Object Tracking
... of neural networks in multiple object tracking is the main reasons are as ...Firstly, neural networks usually need a huge number of training data to learn the large parameters, but we can only ...
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RECENT METHODS FOR OPTIMIZATION OF PLASTIC INJECTION MOLDING PROCESS –A RETROSPECTIVE AND LITERATURE REVIEW
... Artificial neural networks (ANNs) are defined as mathematical models which represent the biological process of a human brain. There are three main components in the ANNs; neurons or processing elements ...
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