Results 31 to 40 of about 1,735,832 (325)
Modeling of Accounting and Non Accounting Items Affecting Shareholders, Wealth: Prediction and Validation [PDF]
The Stock market is one of the markets from which investors try to earn interests. Stock returns are the most important measures for decision making of investors in this market.
azam valizadeh Larijani +1 more
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Modeling of acetosolv pulping of oil palm fronds using response surface methodology and wavelet neural networks [PDF]
Mathematical models based on response surface methodology (RSM) and wavelet neural networks (WNNs) in conjunction with a central composite design were developed in order to study the influence of pulping variables viz. acetic acid, temperature, time, and
Ibrahim, Mazlan +4 more
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APACHE IVa provides typically useful and accurate predictions on in-hospital mortality and length of stay for patients in critical care. However, there are factors which may preclude APACHE IVa from reaching its ceiling of predictive accuracy.
Shuo Feng, Joel A. Dubin
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Statistical post-processing of hydrological forecasts using Bayesian model averaging [PDF]
Accurate and reliable probabilistic forecasts of hydrological quantities like runoff or water level are beneficial to various areas of society. Probabilistic state-of-the-art hydrological ensemble prediction models are usually driven with meteorological ...
Ayari, Mehrez El +2 more
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Mitigating the Impact of Field and Image Registration Errors through Spatial Aggregation
Remotely sensed data are commonly used as predictor variables in spatially explicit models depicting landscape characteristics of interest (response) across broad extents, at relatively fine resolution.
John Hogland, David L.R. Affleck
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Crop yield prediction prior to harvest is important for crop income and insurance projections, and for evaluating food security. Yet, modeling crop yield is challenging because of the complexity of the relationships between crop growth and predictor ...
Angela Kross +6 more
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Watershed models simulate natural hydrological and biogeochemical processes within watersheds as well as quantify the impact of human activities on these processes.
Dmitry V. Kozlov +1 more
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Soft computing techniques, such as artificial neural network (ANN) and multiple linear regression (MLR), have been found useful in the predictive modeling of environmental hazard indicators, even in areas with data scarcity.
Johnbosco C. Egbueri +3 more
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Least‐correlation estimates for errors‐in‐variables models [PDF]
AbstractThis paper introduces an estimator for errors‐in‐variables models in which all measurements are corrupted by noise. The necessary and sufficient condition minimizing a criterion, defined by squaring the empirical correlation of residuals, yields a new identification procedure that we call least‐correlation estimator.
Jun, Byung-Eul, Bernstein, Dennis S.
openaire +2 more sources
Minimum distance estimation of dynamic models with errors-in-variables [PDF]
Empirical analysis often involves using inexact measures of desired predictors. The bias created by the correlation between the problematic regressors and the error term motivates the need for instrumental variables estimation.
Gospodinov, Nikolay +2 more
core +1 more source

