Lightning prediction using radiosonde data
This paper presents a concept of predicting lightning with the data from radiosonde using only a simple back propagation neural network model written in C code. The location of interest in this research is Kuala Lumpur International Airport (KLIA). In this model, the parameters related to wind were...
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| Format: | Conference paper |
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2023
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| _version_ | 1833412645348179968 |
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| author | Weng L.Y. Omar J.B. Siah Y.K. Abidin I.B.Z. Ahmad S.K. |
| author2 | 26326032700 |
| author_facet | 26326032700 Weng L.Y. Omar J.B. Siah Y.K. Abidin I.B.Z. Ahmad S.K. |
| author_sort | Weng L.Y. |
| building | UNITEN Library |
| collection | Institutional Repository |
| content_provider | Universiti Tenaga Nasional |
| content_source | UNITEN Institutional Repository |
| continent | Asia |
| country | Malaysia |
| description | This paper presents a concept of predicting lightning with the data from radiosonde using only a simple back propagation neural network model written in C code. The location of interest in this research is Kuala Lumpur International Airport (KLIA). In this model, the parameters related to wind were disregarded. Preliminary results indicate that this method shows some positive results. Future work should include wind parameters to fully capture all properties for lightning formation, subsequently its prediction. |
| format | Conference paper |
| id | my.uniten.dspace-29717 |
| institution | Universiti Tenaga Nasional |
| publishDate | 2023 |
| record_format | dspace |
| spelling | my.uniten.dspace-297172023-12-28T15:41:46Z Lightning prediction using radiosonde data Weng L.Y. Omar J.B. Siah Y.K. Abidin I.B.Z. Ahmad S.K. 26326032700 24463418200 24448864400 35606640500 25926812900 Artificial intelligence Lightning forecasting Lightning prediction Neural networks Electric load forecasting Lightning Radiosondes Back propagation neural networks C codes Kuala lumpur international airports Radiosonde datum Wind parameters Neural networks This paper presents a concept of predicting lightning with the data from radiosonde using only a simple back propagation neural network model written in C code. The location of interest in this research is Kuala Lumpur International Airport (KLIA). In this model, the parameters related to wind were disregarded. Preliminary results indicate that this method shows some positive results. Future work should include wind parameters to fully capture all properties for lightning formation, subsequently its prediction. Final 2023-12-28T07:41:46Z 2023-12-28T07:41:46Z 2008 Conference paper 2-s2.0-62449251537 https://www.scopus.com/inward/record.uri?eid=2-s2.0-62449251537&partnerID=40&md5=a1367a81aaa94d65392694da7314909f https://irepository.uniten.edu.my/handle/123456789/29717 78 81 Scopus |
| spellingShingle | Artificial intelligence Lightning forecasting Lightning prediction Neural networks Electric load forecasting Lightning Radiosondes Back propagation neural networks C codes Kuala lumpur international airports Radiosonde datum Wind parameters Neural networks Weng L.Y. Omar J.B. Siah Y.K. Abidin I.B.Z. Ahmad S.K. Lightning prediction using radiosonde data |
| title | Lightning prediction using radiosonde data |
| title_full | Lightning prediction using radiosonde data |
| title_fullStr | Lightning prediction using radiosonde data |
| title_full_unstemmed | Lightning prediction using radiosonde data |
| title_short | Lightning prediction using radiosonde data |
| title_sort | lightning prediction using radiosonde data |
| topic | Artificial intelligence Lightning forecasting Lightning prediction Neural networks Electric load forecasting Lightning Radiosondes Back propagation neural networks C codes Kuala lumpur international airports Radiosonde datum Wind parameters Neural networks |
| url_provider | http://dspace.uniten.edu.my/ |