Top PDF An Artificial Neural Network for Data Forecasting Purposes
An Artificial Neural Network for Data Forecasting Purposes
... of artificial neural networks (ANN) in solving the forecast task in the most general case, when the time series are ...feed-forward neural architecture: the nonlinear autoregressive network ...
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Application of Artificial Neural Network for Seasonal Rainfall Forecasting: A Case Study for South Australia
... and forecasting capability of South Australian seasonal rainfall with the aid of climate predictors where maximum of two climate drivers were used instead of single and found some successes regarding correlations ...
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Evaluation of Artificial Immune System with Artificial Neural Network for Predicting Bombay Stock Exchange Trends
... 2. Data refining is very important stage, the Sensing phase filter unnecessary data and decrease data quantity for extracting relevant information from the historical stock ...provides an ...
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Data mining based damage identification using imperialist competi- tive algorithm and artificial neural network
... the network, types of data, number of neurons in each layer, forms of activations, the weights and parameter settings of the ...feed-forward network with different topologies was assessed in order to ...
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A Neural Network Model for Forecasting CO2 Emission
... input data. By training with some known results an artiicial neural network model (ANN), you can perform this task much more ...particular forecasting model whose use is relevant to the ...
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Forecasting Short Term Electricity Price Using Artificial Neural Network and Fuzzy Regression
... function. Neural networks can be multiple layers, these layers called hidden ...layer network. The network is learned in order to have a desired output with the specific group of data, these ...
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Functional Link Artificial Neural Network for Classification Task in Data Mining
... Link Artificial Neural Network (FLANN) model for the task of pattern classification in data ...forward artificial neural network. The network is trained like Back ...
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A method based on neural networks for generating solar radiation map
... on artificial neural networks (ANN) for generating daily GSR data is ...meteorological data throughout the year 2008 belonging to Karaj city in Alborz province of Iran were used to develop GSR ...
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Artificial neural network models: data selection and online adaptation
... as an optimization method where it, as a guided search method, tries to find an acceptable or satisfactory solution in a search ...find an optimal solution, GA starts with an initial ...
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Artificial Neural Network : A Brief Overview
... Artificial Neural Network (ANN) is an information processing paradigm that is inspired by the way biological nervous systems, such as the brain, process ...system. Neural networks, have ...
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An Artificial Neural Network Application for Estimation of Natural Frequencies of Beams
... the data sets are formed and ANN models are ...input data and training function on the models are ...the data, and adjusted R 2 is investigated for determining the inefficient input ...input ...
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Melt ponds on Arctic sea ice determined from MODIS satellite data using an artificial neural network
... enhance data qual- ity for further studies, a data mask with a defined threshold or weighting of involved pixels can be applied after the grid- ding ...low data quality (see ...
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Tourism demand modeling and forecasting with artificial neural network models: The Mozambique case study
... To select the best model it can be regarded as one that has a lower MAPE, which corresponds to the template whose sequence provided overnights is closer to the actual nights, or can select the model with the highest (r) ...
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A Neural Network Approach to Time Series Forecasting
... Airline Data, the Bankruptcy Data, the Electricity Data, the Hong Kong Data, the Nile Data, the Share Data, the Star Data, the Car Data, the Sunspot Data, ...
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Simulação de moagem mista por rede neural artificial Mix grinding simulation by artificial neural network
... on an artificial neural network (multiple-layer perceptron using a back-propagation- like algorithm with ...The data used came from a previous paper entitled “Selective grinding of ...
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Mat. Res. vol.17 número5
... the artificial neural network models are considered as a powerful tool to describe the elevated temperature deformation behavior of ...experimental data from the isothermal compressions of ...
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EUROPEAN UNION’S HISTORY, CULTURE AND CITIZENSHIP
... a forecasting model in predicting tourism demand, as represented by the number of Monthly Guest Nights in Hotels in the North of ...The Artificial Neural Networks (ANN) methodology is employed to ...
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Threshold Prediction of a Cyclostationary Feature Detection Process using an Artificial Neural Network
... in an actual system which is to be realized by an ...of an ANN the weights tends to ...the neural network to learn effectively using the inputs and the targets ...
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APPLYING THE ARTIFICIAL NEURAL NETWORK METHODOLOGY FOR FORECASTING THE TOURISM TIME SERIES
... forecast data of the selected ANN model showed a reasonably close result compared to the target ...world forecasting situations should be the one that is robust and accurate for a long time horizon and thus ...
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Electricity Load Forecasting based on Framelet Neural Network Technique
... becoming an ever more important issue in modern electrical power ...the forecasting of load demand data forms an important component in planning generation schedules in a power ...
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