{"id":3607,"date":"2024-07-08T11:30:59","date_gmt":"2024-07-08T09:30:59","guid":{"rendered":"https:\/\/nepttp.avidakizomba.co.za\/?p=3607"},"modified":"2025-06-09T12:10:30","modified_gmt":"2025-06-09T10:10:30","slug":"application-of-machine-learning-algorithms-for-rainfall-forecasting-in-kwazulu-natal-province-south-africa","status":"publish","type":"post","link":"https:\/\/www.escience.ac.za\/index.php\/2024\/07\/08\/application-of-machine-learning-algorithms-for-rainfall-forecasting-in-kwazulu-natal-province-south-africa\/","title":{"rendered":"Application of Machine Learning Algorithms for Rainfall Forecasting in KwaZulu Natal Province, South Africa"},"content":{"rendered":"<p><strong>Researcher:\u00a0<\/strong>\u00a0Jeremiah Ogunniyi, Sol Plaatje University<br \/><strong>Supervisor:\u00a0<\/strong>\u00a0Dr Ibidun Obagbuwa , Sol Plaatje University<\/p><figure class=\"wp-block-embed is-type-video is-provider-youtube wp-block-embed-youtube wp-embed-aspect-16-9 wp-has-aspect-ratio\"><div class=\"wp-block-embed__wrapper\">\n<iframe title=\"Jerry Ogunniyi - Application of Machine Learning Algorithms for Rainfall Forecasting in....\" width=\"1140\" height=\"641\" src=\"https:\/\/www.youtube.com\/embed\/eVRcJIFqpJc?feature=oembed\" frameborder=\"0\" allow=\"accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share\" referrerpolicy=\"strict-origin-when-cross-origin\" allowfullscreen><\/iframe>\n<\/div><\/figure><p>This study applied three machine learning algorithms namely Linear Regression (LR), Random Forest (RF), and Support Vector Machine (SVM) to predict precipitation in KwaZulu Natal Province, South Africa. The result shows that SVM had the best performance followed by RF and finally LR.<\/p><figure class=\"wp-block-image size-full\"><img fetchpriority=\"high\" decoding=\"async\" width=\"1630\" height=\"778\" src=\"https:\/\/nepttp.avidakizomba.co.za\/wp-content\/uploads\/2024\/10\/Jeremiah-Ogunniyi.png\" alt=\"\" class=\"wp-image-3608\" srcset=\"https:\/\/www.escience.ac.za\/wp-content\/uploads\/2024\/10\/Jeremiah-Ogunniyi.png 1630w, https:\/\/www.escience.ac.za\/wp-content\/uploads\/2024\/10\/Jeremiah-Ogunniyi-600x286.png 600w, https:\/\/www.escience.ac.za\/wp-content\/uploads\/2024\/10\/Jeremiah-Ogunniyi-300x143.png 300w, https:\/\/www.escience.ac.za\/wp-content\/uploads\/2024\/10\/Jeremiah-Ogunniyi-1024x489.png 1024w, https:\/\/www.escience.ac.za\/wp-content\/uploads\/2024\/10\/Jeremiah-Ogunniyi-768x367.png 768w, https:\/\/www.escience.ac.za\/wp-content\/uploads\/2024\/10\/Jeremiah-Ogunniyi-1536x733.png 1536w\" sizes=\"(max-width: 1630px) 100vw, 1630px\" \/><\/figure><p><br \/><\/p>","protected":false},"excerpt":{"rendered":"<p>Researcher:\u00a0\u00a0Jeremiah Ogunniyi, Sol Plaatje UniversitySupervisor:\u00a0\u00a0Dr Ibidun Obagbuwa , Sol Plaatje University This study applied three machine learning algorithms namely Linear Regression (LR), Random Forest (RF), and Support Vector Machine (SVM) to predict precipitation in KwaZulu Natal Province, South Africa. The result shows that SVM had the best<\/p>\n","protected":false},"author":1,"featured_media":4345,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[10],"tags":[],"class_list":["post-3607","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-capstone-projects"],"_links":{"self":[{"href":"https:\/\/www.escience.ac.za\/index.php\/wp-json\/wp\/v2\/posts\/3607","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.escience.ac.za\/index.php\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.escience.ac.za\/index.php\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.escience.ac.za\/index.php\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/www.escience.ac.za\/index.php\/wp-json\/wp\/v2\/comments?post=3607"}],"version-history":[{"count":1,"href":"https:\/\/www.escience.ac.za\/index.php\/wp-json\/wp\/v2\/posts\/3607\/revisions"}],"predecessor-version":[{"id":4346,"href":"https:\/\/www.escience.ac.za\/index.php\/wp-json\/wp\/v2\/posts\/3607\/revisions\/4346"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.escience.ac.za\/index.php\/wp-json\/wp\/v2\/media\/4345"}],"wp:attachment":[{"href":"https:\/\/www.escience.ac.za\/index.php\/wp-json\/wp\/v2\/media?parent=3607"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.escience.ac.za\/index.php\/wp-json\/wp\/v2\/categories?post=3607"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.escience.ac.za\/index.php\/wp-json\/wp\/v2\/tags?post=3607"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}