hybrid neural network model
An Optimized Hybrid Neural Network Model for Detecting Depression among Twitter Users
... optimized hybrid neural network model capable of predicting depression among Twitter users with an accuracy of ...this model could be a valuable tool in depression ...the hybrid ...
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A Hybrid Neural Network Model for Commonsense Reasoning
... a hybrid neural network (HNN) model for commonsense ...language model and a seman- tic similarity model, which share a BERT- based contextual encoder but use different ...
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A hybrid neural network model for predicting kidney disease in hypertension patients based on electronic health records
... Disease prediction, especially the chronic diseases, has received more and more attention from researchers in the biomedical field [19–22]. Early researches mainly focus on the numerical factors including physical ...
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Static Gesture Recognizer Using Hybrid Neural Network
... Sub model of Hybrid Neural Network (ACM_ CNN) is shown Fig ...proposed hybrid neural network model is a composition of Active Contour Model (ACM) and ...
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A hybrid seasonal prediction model for tuberculosis incidence in China
... a model to predict TB epi- demics and to analyze its seasonality in ...artificial neural network [12]. For better forecasting performance, hybrid models which combined two or more single ...
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A Hybrid Neural Network and ARIMA Model for Energy Consumption Forecasting
... artificial neural networks (ANNs) can be adequate in modeling and predicting energy ...ARIMA model cannot deal with nonlinear relationships while the neural network model alone is not ...
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1. A hybrid e-mail spam filtering technique using data mining approach
... new model for classify the spam mails are presented. The proposed data model includes the hybrid approach of classification therefore two classifiers namely Bayesian classifier and back propagation ...
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A Language Independent Neural Network for Event Detection
... a hybrid neural net- work model, which incorporates both bidirectional LSTMs and convolutional neural networks to cap- ture sequence and structure semantic information from specific contexts, ...
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Towards Solving Travelling Salesperson Problem using Hybrid of Genetic Algorithm and Lin Kernighan Algorithm: A Comparative Evaluation with Neural Network Model
... This research dwells on standard TSP. The idea of TSP problem is to find the shortest path of tour starting from a given city, passing once an n city and returning back to the city of take off. The major research problem ...
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Improved Segmentation algorithm using PSO and K means for Basal Cell Carcinoma Classification from Skin Lesions
... Dermoscopy Skin Lesion Image Dataset: Dataset utilized is composed of images from two sources: 1) Atlas of Dermoscopy by Argenziano [14]; 2) ISIC Archive [15]. Images in dataset were acquired randomly where each image ...
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DEVELOPMENT AND COMPARISON OF HYBRID RAINFALL PREDICTION MODEL
... three hybrid rainfall forecasting model: Neural Network and Fuzzy Expert System, Domain Expert System(DES) and Neural Networks (NN) and Combination of Fuzzy Expert System and Data ...
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Modelling and predicting of MODIS leaf area index time series based on a hybrid SARIMA and BP neural network method
... BP neural network and a hybrid method of SARIMA-BP neural network were used for modeling and predicting MODIS LAI time ...SARIMA-BP neural network combined both SARIMA and ...
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Implementation of hybrid classification model in distributed systems for network monitoring
... and Neural Networks classification algorithms identify the pitfalls and propose a new hybrid classification algorithm which is reliable, fast, efficient and robust handling large data ...using Neural ...
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Neural Network Based Model Predictive Control of Batch Extractive Distillation Process for Improving Purity of Acetone
... A waste solvent mixture of acetone-methanol water from a pharmaceutical plant, minimum boiling azeotrope property, is difficult to separate by conventional batch distillation. Consequently, to improve effectiveness of ...
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A Hybrid Model using Artificial Neural Network and Genetic Algorithm for Degree of Injury Determination
... the hybrid model which is Artificial Neural Network and Genetic Algorithm techniques by using critical features obtained from previous studies to increase the accuracy of the degree of injury ...
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Estimation of LLE Data for Binary Systems of N-Formylmorpholine with Alkanes Using Artificial Neural Network–Genetic Algorithm (ANN–GA) Model
... the hybrid neural network and genetic algorithm were successfully applied to estimate the LLE ...forward neural network. The best architecture for the network has one hidden ...
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NeuroSVM: A Graphical User Interface for Identification of Liver Patients
... a hybrid NeuroSVM model was developed using SVM and feed-forward artificial neural network ...The hybrid model was tested for its performance using statistical parameters like ...
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Application research of convolution neural network in image classification of icing monitoring in power grid
... convolution neural network, this paper applies it to the detection of power network ...power network icing detection image based on convolution neural network is proposed, which ...
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Soft Computing Stock Market Price Prediction for the Nigerian Stock Exchange
... prediction model. Two soft computing models- Artificial Neural Network (ANN) and Fuzzy Artificial Neural Network (FANN) hybrid model were used to forecast the next day’s ...
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Multiple linear regression and neural network for electric load forecasting
... best model in modeling the data. Thus, developing a hybrid model that combines different models can be a good option to address ...this. Hybrid model also has the advantage of embracing ...
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