NARX model
System identification and data-driven forecasting of AE index and prediction uncertainty analysis using a new cloud-NARX model
... cloud-NARX model was applied to the modeling and forecasting of AE ...best NARX model. The cloud-NARX model outperforms the previous models, for example, ...cloud-NARX ...
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Prediction of Landslide Displacement using NARX Model
... of NARX neural network for landslide displacement ...as NARX can reflect relationship among ...and NARX has been performed using MSE (Minimum Square ...
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New bound characteristics of NARX model in the frequency domain
... the NARX model including the GFRFs and the output spectrum are investigated in this ...the model parameters and the boundedness of the system frequency response functions, and provide a significant ...
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A novel logistic-NARX model as a classifier for dynamic binary classification
... and NARX) and other similar and related model types have been preferably applied to handle diverse data driven modeling problems due to their easy-to-compute linear-in-the-parameters structure, which allows ...
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Predictioin of fruit quality using near-infrared VIA NARX model
... Pada masa kini, kesedaran tentang kesihatan dan keselamatan dikalangan pengguna telah meningkat. Senario ini mengakibatkan para pengguna sanggup mengeluarkan kos yang tinggi atau membayar lebih untuk produk buah yang ...
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On-line prediction remaining useful life for ball bearings via grey NARX
... (NARX) model to forecast the remaining useful life of ball bearings through health index based on big vibration data ...hybrid NARX model evaluation index are ...the model presented in ...
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Modelling and Prediction of Global Magnetic Disturbance in Near-Earth Space: a Case Study for Kp Index using NARX Models
... nificant model terms that are shared by all the models, regardless of the time horizon of ...logistic-NARX model may be more appropriate to deal with the Kp prediction problem where the output signal ...
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Sensitivity based selection of inputs and delays for NARX models
... (NARX) model is ...the NARX network without any significant performance ...for NARX than for simple feedforward neu- ral network, because NARX is more prone to overfitting and has ...
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The Performance of Binary Artificial Bee Colony (BABC) in Structure Selection of Polynomial NARX and NARMAX Models
... The correlation tests measure the similarity between two signals [41] across different lags. For the residuals to appear as white noise, all correlation coefficients (except for lag zero in autocorrelation tests) should ...
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Online multistep ahead inundation depth forecasts by recurrent NARX networks
... R- NARX models, the scatter plots of the simulated versus fore- casted flood depths of site 2 (one-, three- and six-hour-ahead) in the testing data sets are shown in ...R-NARX model, almost all pairs ...
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Wind Speed & Power Forecasting using Artificial Neural Network (NARX) for New York Wind Energy Farm
... By using the data sets of wind speed, direction, temperature and historical data of wind speed, power as input the future value of speed and power is forecasted. The data of 2010 & 2011 of New York wind farm is used ...
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Rainfall Prediction with AMSR-E Soil Moisture Products Using SM2RAIN and Nonlinear Autoregressive Networks with Exogenous Input (NARX) for Poorly Gauged Basins: Application to the Karkheh River Basin, Iran
... the NARX model, the full study period is split into a training (1 January 2003 to 31 September 2005) and a testing (1 September 2005 to 30 September 2006) ...the NARX- model the values are ...
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Multi-Layer Perceptron (MLP)-Based Nonlinear Auto-Regressive with Exogenous Inputs (NARX) Stock Forecasting Model
... (NARX) model was used to predict the prices of the Apple ...The NARX model is a system identification model that constructs a mathematical model from the dynamic input/output ...
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IBTC Model: A Model for classification of Queries
... IBTC model for queries is a model for text classification when the input is in the form of query, where each query contains various ...IBTC model for queries is a model which covers both task ...
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Predicting Category Intuitiveness With the Rational Model, the Simplicity Model, and the Generalized Context Model
... Simplicity model predictions were given as codelength values, so that a lower codelength indicates a more intuitive ...simplicity model is not item coordinates, but rather information of which pairs of ...
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A New Intercomprehension Model: Reservoir Model
... Intercomprehension is a form of communication in which each person uses his/her own language and understands that of the other(s). To promote this concept and to help European learners to acquire intercomprehensive ...
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P-model Alternative to the T-model
... The T-model illustrated in diagram one consists of several levels. The D-structure (deep struc- ture) level is supposed to hold a given sentence in a primitive form. The D-structure level cannot be the same as the ...
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A model driven approach to model transformations
... OMG’s Model Driven Architecture (MDA) initiative has been the focus of much attention in both academia and industry, due to its promise of more rapid and consistent software development through the increased use ...
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A model–model and data–model comparison for the early Eocene hydrological cycle
... a model intercomparison of early Eocene warmth, EoMIP, based on an ensemble of 12 Eocene simulations undertaken in four fully coupled atmosphere–ocean climate models, a summary of which is given in Table ...
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Non-model model organisms
... major model or- ganisms, while convenient for studying many aspects of biology, weren’t necessarily the best systems for all pos- sible ...carefully. Model organisms were known for many of these ...
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