IRF - AR Model for Short-Term Prediction of Ship Motion
نویسندگان
چکیده
Reliable short-term prediction of ship motions improves the safety in ship motion related special operations, where autoregressive (AR) model is extensively used as its advantages like convenient in real-time identification and high adaptive nature. Order selection is the most critical and difficult part in the identification of AR model. Conventionally, the model order is determined by applying Akaike information criterion (AIC), Bayesian information criterion (BIC) or final prediction error (FPE) criterion, which are rather time consuming and sample frequency sensitive. In this paper, a novel order selection approach is developed based on ship impulse response function (IRF) and the AR model using IRF order selection is designated as IRF-AR model. Simulation results of S175 container ship show the superiority of IRF-AR model to conventional model in forecast accuracy, efficiency and algorithm adaptation.
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