English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

Significant wave height forecasting is a key problem in ocean data analytics.Predicting the significant wave height is crucial for estimating the energyproduction from waves. Moreover, the timely prediction of large waves isimportant to ensure the safety of maritime operations, e.g. passage of vessels.We frame the task of predicting extreme values of significant wave height as anexceedance probability forecasting problem. Accordingly, we aim at estimatingthe probability that the significant wave height will exceed a predefinedthreshold. This task is usually solved using a probabilistic binaryclassification model. Instead, we propose a novel approach based on aforecasting model. The method leverages the forecasts for the upcomingobservations to estimate the exceedance probability according to the cumulativedistribution function. We carried out experiments using data from a buoy placedin the coast of Halifax, Canada. The results suggest that the proposedmethodology is better than state-of-the-art approaches for exceedanceprobability forecasting.

Exceedance Probability Forecasting via Regression for Significant Wave Height Prediction