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We describe the use of ensemble methods to build models for time series prediction.
Literature review clearly reveals that models for time loss and cost in vehicle assembly line are not attempted in detail.
The unadjusted and multivariable adjusted hazard ratios (HR) foracute kidney injury (AKI) in time-stratified Cox models for time to death in three-year follow-up.
In a recent and comprehensive comparison on the M3 dataset for the major ML models for time series forecasting, Ahmed et al.
In this paper we will give an overview of research in field of computer science where fireflies in nature are used as role models for time synchronization.
In this paper we introduce the Kumaraswamy autoregressive moving average models (KARMA), which is a dynamic class of models for time series taking values in the double bounded interval (a,b) following the Kumaraswamy distribution.
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The modeling results substantiate the efficacy of such different ZD models for time-varying reciprocal solving.
Surrogate interpolation models for time-consuming computer experiments are being increasingly used in scientific and engineering problems.
Both theoretical analysis and modeling results substantiate the efficacy of the proposed ZNN models for time-varying matrix square roots finding.
The proper orthogonal decomposition (POD) method (see [9 13]) is an effective means to reduce the degrees of freedom of numerical models for time-dependent PDEs and alleviate load calculating and the accumulation of truncation errors in the computational process.
As a first step towards the synthesis of controllers reconciling both qualitative and quantitative specifications, we investigate in this paper the use of symbolic models for time-optimal controller synthesis.
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