scholarly journals Two-dimensional linear prediction model-based decorrelation method

1989 ◽  
Vol 11 (6) ◽  
pp. 661-665 ◽  
Author(s):  
Z. Lin ◽  
Y. Attikiouzel
Keyword(s):  
Prediction Model ◽  
Linear Prediction ◽  
Two Dimensional ◽  
Model Based ◽  
Linear Prediction Model

scholarly journals A non-linear prediction model for ageing foetal and neonatal sheep reveals basic issues in early neolithic husbandry

2021 ◽  
pp. 105344
Author(s):  
Nadja Pöllath ◽  
Ricardo García-González ◽  
Sevag Kevork ◽  
Ursula Mutze ◽  
Michaela I. Zimmermann ◽  
...  
Keyword(s):  
Prediction Model ◽  
Linear Prediction ◽  
Early Neolithic ◽  
Non Linear ◽  
Linear Prediction Model

Multi-day flow forecasting using the Kalman filter

1991 ◽  
Vol 18 (2) ◽  
pp. 320-327 ◽  
Author(s):  
Murray A. Fitch ◽  
Edward A. McBean
Keyword(s):  
Kalman Filter ◽  
Prediction Model ◽  
Linear Prediction ◽  
Measured Data ◽  
System Model ◽  
Parameter Estimates ◽  
Model Parameters ◽  
Forecasting Performance ◽  
Optimal Forecasting ◽  
Linear Prediction Model

A model is developed for the prediction of river flows resulting from combined snowmelt and precipitation. The model employs a Kalman filter to reflect uncertainty both in the measured data and in the system model parameters. The forecasting algorithm is used to develop multi-day forecasts for the Sturgeon River, Ontario. The algorithm is shown to develop good 1-day and 2-day ahead forecasts, but the linear prediction model is found inadequate for longer-term forecasts. Good initial parameter estimates are shown to be essential for optimal forecasting performance. Key words: Kalman filter, streamflow forecast, multi-day, streamflow, Sturgeon River, MISP algorithm.

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