| Yazarlar (6) |
Harsh Taneja
|
|
Vanita Jain
|
|
Achin Jain
|
|
Arun Kumar Dubey
|
|
Müslüm Cengiz Taplamacioglu
Gazi Üniversitesi, Türkiye |
Dr. Öğr. Üyesi Merve DEMİRCİ
Kafkas Üniversitesi, Türkiye |
| Özet |
| Weather forecasting is a practice of science and innovation to predict environmental conditions at a particular location using data of previous days' weather conditions. This study aims to develop a novel algorithm to predict the weather and furnish the most accurate forecast. To achieve this, initially the historical weather data for the region has been collected and later that data has been used to train and test the algorithms for better forecasting. The gathered data set has been split in the ratio 80: 20 for testing and training respectively. This research work proposes following two algorithms for weather forecasting: Linear Regression; and Artificial Neural Network. The performances of the algorithms have been compared using numerous performance metrics. Linear Regression model demonstrates values MSE= 0.00977262 and RMSE= 0.0988565, while ANN technique depicts the performance as MSE= 0.001260 and RMSE= 0.035507. ANN has illustrated better performance and has proved to be more effective in weather forecasting. |
| Anahtar Kelimeler |
| Makale Türü | Özgün Makale |
| Makale Alt Türü | SCOPUS dergilerinde yayınlanan tam makale |
| Dergi Adı | International Journal on “Technical and Physical Problems of Engineering” (IJTPE) |
| Dergi ISSN | 2077-3528 Scopus Dergi |
| Dergi Tarandığı Indeksler | Scopus |
| Makale Dili | İngilizce |
| Basım Tarihi | 06-2024 |
| Cilt No | 16 |
| Sayı | 2 |
| Sayfalar | 303 / 312 |
| Makale Linki | https://www.iotpe.com/IJTPE/IJTPE-2024/IJTPE-Issue59-Vol16-No2-Jun2024/39-IJTPE-Issue59-Vol16-No2-Jun2024-pp303-312.pdf |
