neural network based model training
Neural Network based Software Effort Estimation: A Survey
... basis neural network and regression neural networks to predict software development ...basis neural networks model performs more accurately for effort ...
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Prediction of Gum Disease Severity on the basis of Symptoms and Risk factors using Neural Network
... computing based decision making model is a new era in the field of dentistry and for common ...artificial neural network mode is helpful in clinical ...the neural network ...
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Research on Financial Early Warning of Listed Corporation Based on SOM Fusion BP Neural Network
... the neural network models as above show that when the early-warning model of the final model and the samples of input data contain non-ST and ST sample objects are categorized into two ...
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A SHORT-TERM TRAFFIC FLOW FORECASTING METHOD BASED ON STATE IDENTIFICATION.
... method based on knowledge discovery, Include the methods of neural network, Nonparametric regression, Support vector machine ...(SVM). Neural network method is to use a lot of ...
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A NEURAL NETWORK MODEL FOR SHORT TERM PREDICTION OF SURFACE OZONE AT TROPICAL CITY
... Neural network techniques have recently become the focus of much attention as they can handle the complex and non-linear problems better than the conventional statistical ...techniques. Neural ...
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PREDICTION OF SITE RESPONSE SPECTRUM UNDER EARTHQUAKE VIBRATION USING AN OPTIMIZED DEVELOPED ARTIFICIAL NEURAL NETWORK MODEL
... code based on several different training algorithms as well as various activation transfer functions have been developed to find an optimized ANN model to predict the site response spectra for a ...
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Neural Network Based Rainfall Prediction
... is based on artificial neural ...to model complex relationships between inputs and outputs or to find patterns in the given data ...The neural network based system provides ...
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A Comparative Analysis of Neural Network Based Short Term Load Forecast Models for Anomalous Days Load Prediction
... (LM) training method of NN. Analysis shows that MAPE of LM based forecast model is less in morning time and as the time is passed of a day, the MAPE becomes ...ANN model, the type of day ...
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Co-Attention Based Neural Network for Source-Dependent Essay Scoring
... Previous research in AES needed feature engineer- ing. In very early work, Page (1968) developed an AES tool named Project Essay Grade (PEG) by only using linguistic surface features. A more re- cent well-known AES ...
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Structured Training for Neural Network Transition Based Parsing
... the neural network directly for beam search to using the acti- vations from all layers as features in the structured ...maximum-entropy model was used to model the distribution over possible ...
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Research on Early Warning Model of College Students' Psychological Crisis Based on Genetic BP Neural Network
... Artificial Neural Networks (ANNs) in the application of psychology ...evaluation model of post-disaster psychological crisis based on principal component analysis and neural network, ...
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Recursive Gauss Newton based training algorithm for neural network modelling of an unmanned rotorcraft dynamics
... This paper presents a recursive Gauss-Newton based training algorithm to model the attitude dynamics of a small scale rotorcraft based unmanned aerial system using the neural network NN [r] ...
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Formation Smart Data Science for Automated Analytics of Modeling of Scientific Experiments
... on neural network learning, particularly the development and validation of machine learning ...conduct training, and the other will test the algorithm, checking how accurately the model of the ...
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Prediction of Engineered Cementitious Composite Material Properties Using Artificial Neural Network
... proportion based on uniaxial tensile strength and strain, the correlation between these parameters were ...ECC based on experimental results, Artificial Neural Network (ANN) was ...used. ...
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Survey of Researches on Chinese Sentiment Analysis Based on Deep Learning
... convolution neural network structure model to perform sentiment analysis of micro-blogging ...convolution neural network, which has achieved better performance than the current ...
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LSTMs with Attention for Aggression Detection
... a neural network based model which has LSTM units followed by an attention unit to embed the given social media post and training a classifier to detect ...
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Human-level Moving Object Recognition from Traffic Video
... low network learning efficiency, and falling to local optimal. Deep neural network is a multiple neural network learning model based on deep learning, which learns some ...
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Design of Low Noise Amplifier of IRNSS using ANN
... measurements. Training is done to determine neural network weights w such that the neural model output best matches the training ...trained neural network ...
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Improving of Crystal Size Distribution Control Based on Neural Network Based Hybrid Model for Purified Terephthalic Acid Batch Crystallizer
... feedforward neural network with the structure consisting of 4 nodes in the input layer and 2nodes at the output layer as shown in ...the training and validation data sets generated from the ...
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The Training and Application of RBF Neural Network Based on GWO
... RBF neural network, it is important and difficult to determine the three vectors: the hidden center vector Φ whose dimension is Nr*Nh, Gaussian RMS width vector Θ whose dimension is Nh*1 and the ...
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