Results 121 to 130 of about 1,758,719 (322)
Use of Stability and Seasonality Analysis for Optimal Inventory Prediction Models
Inventory prediction and management is a key issue in a retail store. There are a number of inventory prediction techniques. However, it is difficult to identify a time series prediction model for inventory forecasting that provides uniformly good ...
Zhang Peng, Joshi Manish, Lingras Pawan
doaj +1 more source
One-step Prediction of Financial Time Series [PDF]
Srichander Ramaswamy
openalex +1 more source
Prediction with univariate time series models: The Iberia case [PDF]
In this paper we model the monthly number of passengers flying with the Spanish airline IBERIA from January 1985 to December 1992 and predict future values of the series up to October 1994.
Ester Ruiz, Fernando Lorenzo
core
Abstract Purpose To generate high‐quality stereotactic radiosurgery (SRS) plans for single cranial lesions using 4Pi planning technique and compare these to our clinical “status quo” plans. Methods Eighteen vestibular schwannoma (VS) patients previously planned with Varian Eclipse RapidArc and treated on a Varian TrueBeam using 6FFF MV photon beams ...
Ganesh Narayanasamy+4 more
wiley +1 more source
Time series prediction based on the Relevance Vector Machine with adaptive kernels [PDF]
Joaquin Quiñonero-Candela+1 more
openalex +3 more sources
Dual-orthogonal radial basis function networks for nonlinear time series prediction [PDF]
S.A. Billings, Xia Hong
openalex +1 more source
Impact of respiratory motion on dose distribution in SIB‐SBRT for lung cancer
Abstract Purpose Respiratory motion is a major source of dose uncertainty in lung cancer radiotherapy. The dose distribution of simultaneous integrated boost‐stereotactic body radiotherapy (SIB‐SBRT) is inhomogeneous and is significantly impacted by respiratory motion for lung cancer. The effect of respiratory motion on SIB‐SBRT was investigated with a
Lingling Liu+7 more
wiley +1 more source
Precision‐Optimised Post‐Stroke Prognoses
ABSTRACT Background Current medicine cannot confidently predict who will recover from post‐stroke impairments. Researchers have sought to bridge this gap by treating the post‐stroke prognostic problem as a machine learning problem, reporting prediction error metrics across samples of patients whose outcomes are known.
Thomas M. H. Hope+4 more
wiley +1 more source
EEG Response to Sedation Interruption Complements Behavioral Assessment After Severe Brain Injury
ABSTRACT Objective Accurate assessment of the level of consciousness and potential to recover in patients with severe brain injury underpins crucial decisions in the intensive care unit but remains a major challenge for the clinical team. The neurological wake‐up test is a widely used assessment tool. However, many patients' behavioral responses during
Charlotte Maschke+12 more
wiley +1 more source
Dimension reduction of technical indicators for the prediction of financial time series - Application to the BEL20 Market Index [PDF]
Amaury Lendasse+4 more
openalex +1 more source