Matches in SemOpenAlex for { <https://semopenalex.org/work/W4366606029> ?p ?o ?g. }
Showing items 1 to 58 of
58
with 100 items per page.
- W4366606029 abstract "This research is aimed at preventing broadcast equipment from lightning damage. Inview of the location in which my broadcast outfit is located (located in a valley; some few meters above sea level in the Confluence of Lokoja Kogi State Nigeria). Several improvement of earthing and installation of lightning arresting facilities, there has not been significant change protecting broadcast equipment from lightning. The solution I proffered is to isolate all electrical connection from equipment. Lightning as a natural phenomenon is very unpredictive and destructive which can occur during transmission. How do we know the day and time distructive lightning will come? The answer is to develop a lightning prediction system that is accurate. When lightning lead time is known, personnel on duty will be alerted to isolate all broadcast equipment from the mains and central earth connection. Since the lightning prediction system has to be localized. Deployment of machine learning algorithm is most appropriate. The use of ten(10) years Weather Numerical Values(2012-2022) such as rainfall, atmospheric pressure, relative humidity, temperature and lightning records which are gotten from Nigeria Meteorological Agency (NIMET), Lokoja Area Office, Kogi State. This parametization are factors that are used to work on the lightning forecast system as lightning will occur at their certain threshold values. The model is intended to be deployed on web application. Prediction model can be localized to support Numerical Weather Prediction in any environment in Nigeria." @default.
- W4366606029 created "2023-04-23" @default.
- W4366606029 creator A5039474063 @default.
- W4366606029 creator A5039582396 @default.
- W4366606029 creator A5054403948 @default.
- W4366606029 date "2023-04-20" @default.
- W4366606029 modified "2023-10-18" @default.
- W4366606029 title "Development of a Lightning Prediction Model Using Machine Learning Algorithm: Survey." @default.
- W4366606029 doi "https://doi.org/10.48185/jaai.v4i1.727" @default.
- W4366606029 hasPublicationYear "2023" @default.
- W4366606029 type Work @default.
- W4366606029 citedByCount "0" @default.
- W4366606029 crossrefType "journal-article" @default.
- W4366606029 hasAuthorship W4366606029A5039474063 @default.
- W4366606029 hasAuthorship W4366606029A5039582396 @default.
- W4366606029 hasAuthorship W4366606029A5054403948 @default.
- W4366606029 hasConcept C11413529 @default.
- W4366606029 hasConcept C121332964 @default.
- W4366606029 hasConcept C147947694 @default.
- W4366606029 hasConcept C153294291 @default.
- W4366606029 hasConcept C163258240 @default.
- W4366606029 hasConcept C182236062 @default.
- W4366606029 hasConcept C205649164 @default.
- W4366606029 hasConcept C39432304 @default.
- W4366606029 hasConcept C41008148 @default.
- W4366606029 hasConcept C62520636 @default.
- W4366606029 hasConcept C69398868 @default.
- W4366606029 hasConcept C80316258 @default.
- W4366606029 hasConceptScore W4366606029C11413529 @default.
- W4366606029 hasConceptScore W4366606029C121332964 @default.
- W4366606029 hasConceptScore W4366606029C147947694 @default.
- W4366606029 hasConceptScore W4366606029C153294291 @default.
- W4366606029 hasConceptScore W4366606029C163258240 @default.
- W4366606029 hasConceptScore W4366606029C182236062 @default.
- W4366606029 hasConceptScore W4366606029C205649164 @default.
- W4366606029 hasConceptScore W4366606029C39432304 @default.
- W4366606029 hasConceptScore W4366606029C41008148 @default.
- W4366606029 hasConceptScore W4366606029C62520636 @default.
- W4366606029 hasConceptScore W4366606029C69398868 @default.
- W4366606029 hasConceptScore W4366606029C80316258 @default.
- W4366606029 hasIssue "1" @default.
- W4366606029 hasLocation W43666060291 @default.
- W4366606029 hasOpenAccess W4366606029 @default.
- W4366606029 hasPrimaryLocation W43666060291 @default.
- W4366606029 hasRelatedWork W191847120 @default.
- W4366606029 hasRelatedWork W1995574193 @default.
- W4366606029 hasRelatedWork W2009005855 @default.
- W4366606029 hasRelatedWork W2038487875 @default.
- W4366606029 hasRelatedWork W2531389475 @default.
- W4366606029 hasRelatedWork W263146809 @default.
- W4366606029 hasRelatedWork W3166459492 @default.
- W4366606029 hasRelatedWork W3201164092 @default.
- W4366606029 hasRelatedWork W340830119 @default.
- W4366606029 hasRelatedWork W779845119 @default.
- W4366606029 hasVolume "4" @default.
- W4366606029 isParatext "false" @default.
- W4366606029 isRetracted "false" @default.
- W4366606029 workType "article" @default.