non-linear neural network model
Implementation of Artificial Neural Network for Short Term Load Forecasting
... artificial neural network ...artificial neural network is widely used, as it posses the ability to solve non linear relationship between load and the factors such as temperature, ...
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Back propagation neural network and non-linear regression models for dengue outbreak prediction
... However, study on dengue outbreak prediction is only useful if a model, which enables a good prediction upon these criteria, is selected. Unfortunately, no such study has been done to predict the dengue outbreak ...
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Comparative study of static and dynamic neural network models for nonlinear time series forecasting
... and non-linear relations, the use of flexible non-linear models, such as neural network models, in modeling and forecasting the market indexes can yield impressive results ...
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A Three-Step Neural Network Artificial Intelligence Modeling Approach for Time, Productivity and Costs Prediction: A Case Study in Italian Forestry
... ANN model was developed using a Multi- Layer Feed Forward Networks (MLFN) structure, the method often used for function approximation (Mossalam and Arafa ...of non-linear static or dynamic systems ...
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A neural network auto regression model to forecast per capita disposable income
... a linear and non- linear ...NNAR model is used for forecasting purpose. Neural network models have been applied to forecast electric load (Park, El- Sharkawi, Marks II, Atlas and ...
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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
... tremendous non-linearity and the linear statistical methods do not behave sufficiently for modeling ...artificial neural network along with BCL2 inhibitors for regression ...
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Designing Dynamic Neural Network For Non-Linear System Identification
... Artificial Neural Network (ANN) is a mathematical model that tries to simulate the structure and functionalities of biological neural ...artificial neural network is artificial ...
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Robust artificial neural network for reliability and sensitivity analysis of complex non-linear systems
... mathematical model of the Site Ion eXchange Effluent Plant (SIXEP)(see [33]) situated on the nuclear fuel reprocessing and decommissioning site at Sellafield, ...
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Agricultural data prediction by means of neural network
... multi-layer neural network ...several non-linear regression models, the usefulness of which has been tested and published several times in the specialized ...A neural network ...
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Neural network modelling of non linear hydrological relationships
... NN model to capture non-linear effects within the non- linearity range employed in traditional rainfall-runoff models of the type that are widely used in operational flood forecast- ing ...
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Feature Selection with Non Linear PCA: A Neural Network Approach
... Artificial neural networks (ANNs) [10] [11] are, among the tools capable of learning from examples, those with the greatest capacity for generalization, be- cause they can easily manage situations not foreseen ...
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Non Linear Text Regression with a Deep Convolutional Neural Network
... We find that both text and meta data con- tain complementary signals with some informa- tion overlap between them. This confirms the find- ing of Bitvai and Cohn (2015) on another text re- gression problem. The meta ...
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EFFICIENT SCHEDULING OF WORKFLOW IN CLOUD ENVIORNMENT USING BILLING MODEL AWARE TASK CLUSTERING
... function neural network model The radial basis function neural network (RBFNN)[8] has a feed forward architecture with an input layer, a hidden layer and an output layer as shown in ...
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Comparison of artificial neural network and multivariate regression methods in prediction of soil cation exchange capacity (Case study: Ziaran region)
... multivariate linear regression and neural network model (feed-forward back- propagation network) were employed to develop a pedotransfer function for predicting soil cation exchange ...
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A machine learning driven sky model
... alternative model for sky illumination based on machine ...the non-linear mapping of sun and view direction to radiance values using a single layer Artificial Neural ...The network is ...
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A NEURAL NETWORK MODEL FOR SHORT TERM PREDICTION OF SURFACE OZONE AT TROPICAL CITY
... The non-linear relationship of surface ozone with solar radiation has been mentioned by Bravo et ...dispersion model and the inadequacy of this model for controlling ...the neural ...
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Non Linear Feedback Neural Network for Solution of Quadratic Programming Problems
... to linear constraints on these ...artificial neural networks (ANN's) which can be considered as an analog computer relying on a highly simplified model of neurons ...Hopfield neural ...
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Multi-Interactive Memory Network for Aspect Based Multimodal Sentiment Analysis
... deep neural network with multiple layers to learn the deep representations of data with multi-level abstractions (LeCun, Bengio, and Hinton ...the linear layer used in pre- vious work (Tang, Qin, and ...
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Conjugate gradient neural network in prediction of clay behavior and parameters sensitivities
... the non-linearity ...the non-linearity is not required for artificial neural network ...artificial neural network model, the degree of non-linearity can be also ...
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Artificial Neural Network and Non-Linear Regression: A Comparative Study
... The standard deviation of the observed scaled air for the test case is 0.1622. It can be seen that the RMSE values for both the cases is smaller than the standard deviation for the observed data. The standard deviation ...
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