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

Troposphere and the first stratum of the stratosphere are intensely utilized atmosphere layers for the aviation activities. Due to the different performances, capabilities, designs, and equipment of the aerial vehicles, meteorological weather events that occur in the troposphere affect these vehicles at different levels during their aeronautical activities. Although simple aircrafts are more sensitive to the effects of meteorological events, they are especially preferred by flight training organizations (FTOs) in pilotage training when they are considered in terms of maintenance and equipment costs. In cases where inexperienced pilot candidates and simple aircrafts that are more vulnerable to weather events come together, analysis and prediction of meteorological parameters becomes more important in terms of preventing accidents and reducing risks, as well as proper planning for flight and maintenance. The purposes of this study are, first, to derive flight availability time-series for two different types of aircraft according to visual flight rules by using Meteorological Terminal Air Report (METAR), and then to establish and evaluate a prediction model by using Time-Delay Neural Networks (TDNNs).

Time-Series Prediction for Amount of Airworthiness Based on Time-Delay Neural Networks