The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.
The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.
Patent No.:
Date of Patent:
Feb. 19, 2008
Filed:
Aug. 29, 2005
Chunbao Zhu, Singapore, SG;
Chunbao Zhu, Singapore, SG;
Nanyang Polytechnic, Singapore, SG;
Abstract
The present invention provides a Chinese lunar calendar-based tidal prediction system and method that generate tidal predictions using empirical prediction models, wherein the empirical prediction models are generated using Genetic Algorithms-based regression analysis for a given set of observed tidal data collected at a water level station during a period of one year which is referred as reference year. In one aspect of the present invention, there is provided a tidal prediction system comprising an electronic device having a memory capacity as a storage medium for storing input, intermediate, and output information, and a processing capacity for executing embedded programs; a regression model creator program; and a tidal height predictor program; wherein both of programs are implemented in the electronic device. In another aspect of the present invention, there is provided a Chinese lunar calendar-based tidal prediction method comprising the steps of inputting a prediction date of which the tidal prediction is requested for a location; selecting a reference year from which the tidal prediction for the prediction date will be made; obtaining actual tidal data in the reference year near the location, wherein the actual tidal data is formatted according to Chinese lunar calendar; generating a regression prediction model for the actual tidal data of the reference year by performing genetic algorithm evolution of the actual tidal data; and predicting the tidal heights for the requested prediction date in accordance with the regression prediction model.
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