Open AccessStudy on the selection and optimization of key elements in the offshore wave prediction
Author(s) -
Dongzi li
Publication year - 2020
Publication title -
iop conference series. materials science and engineering
Language(s) - English
Resource type - Journals
eISSN - 1757-899X
pISSN - 1757-8981
DOI - 10.1088/1757-899x/780/3/032053
Subject(s) - key (lock) , sorting , selection (genetic algorithm) , computer science , process (computing) , analytic hierarchy process , data mining , scheme (mathematics) , extension (predicate logic) , machine learning , operations research , algorithm , engineering , mathematics , mathematical analysis , computer security , programming language , operating system
The accuracy of inshore wave prediction is closely related to the key elements selected in the prediction. There is a problem of selecting and sorting the key information needed in wave forecasting. This paper combines AHP with DEA to build a new evaluation model of selecting scheme. By calculating the relative weight of the key information in each selecting scheme and calculating the relative efficiency value of the model, the importance sorting of the elements needed in wave forecasting is obtained, and the specific selection scheme is verified by an example Application. The established AHP-EDA model has the value of trial and extension in supporting the key element selection process of wave prediction.