A Syntactic Pattern Recognition Approach to Wave Analysis

James Bateman


Supervised by Paul L Rosin; Moderated by David J Humphreys

Safety is of constant concern to boat pilots. While there are good mobile applications that can give an approximation of current weather conditions, and some that can track other local vessels, there are no systems which address the safety of current wave conditions. This paper presents an application of syntactic pattern recognition to the analysis of ocean waves in the context of boat safety. The solution uses a boat’s dimensions to build a parser that is capable of classifying a time series constructed from 1-dimensional, surface-height ocean wave data, as would be collected by a sensor on the prow of a boat, presented in the form of a sentence that is produced by a tokeniser. Two distinct models of parsing are described and implemented in order to contrast their distinguishing features in terms of precision and performance. Attribute Grammars are an augmented form of Context Free Grammars and were selected in the first model due to their powerful ability to pass values around an abstract syntax tree. Parsing Expression Grammars were selected in the second model and differ fundamentally from Context Free Grammars in that the choice of their operation is ordered. Methods of preprocessing wave data were discussed and implemented, along with methods of extracting peaks and troughs from wave data. A comparative study of these contrasting parsing methods is presented, and their performance is evaluated. The Parsing Expression Grammar was found to be a more efficient categorising method than the Attribute Grammar, but only by a matter of 2%. However, the Attribute grammar produces false positives at a rate of three times less than the Parsing Expression Grammar, making it more applicable to the task. Possible applications of the technology in a production capacity and other future work are also discussed.

Initial Plan (08/02/2021) [Zip Archive]

Final Report (14/05/2021) [Zip Archive]

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