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Content available On Nautical Observation Errors Evaluation
EN
Mathematical Theory of Evidence (MTE) enables upgrading models and solving crucial problems in many disciplines. MTE delivers new unique opportunity once one engages possibilistic concept. Since fuzziness is widely perceived as something that enables encoding knowledge thus models build upon fuzzy platforms accepts ones skill within given field. At the same time evidence combining scheme is a mechanism enabling enrichment initial data informative context. Therefore it can be exploited in many cases where uncertainty and lack of precision prevail. In nautical applications, for example, it can be used in order to handle data feature systematic and random deflections. Theoretical background was discussed and computer application was successfully implemented in order to cope with erroneous and uncertain data. Output of the application resulted in making a fix and a posteriori evaluating its quality. It was also proven that it can be useful for calibrating measurement appliances. Unique feature of the combination scheme proven by the author in his previous paper, enables identifying measurement systematic deflection. Based on the theorem the paper aims at further exploration of practical aspects of the problem. It concentrates on reduction of hypothesis frame reduction and random along with systematic errors identifications.
EN
Plenty of various quality data are available to the officer of watch. The data of various qualities comes from different navigational aids. This kind of data creates new challenge regarding information association. The challenge is met by Mathematical Theory of Evidence. The theory delivers methods enabling combination of various sources of data. Results of association have informative context increased. Associated data enable the navigator to refine his position and his status regarding dangerous places. The procedure involves uncertainty, ambiguity and vague evidence. Imprecise and incomplete evidence can be combined using extended Dempster-Shafer reasoning scheme.
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