Sensory Precipitation Forecast Using Artificial Neural Networks and Decision Trees

Hakkı Fırat ALTINBİLEK; Hakan NAR; Sefa AKSU; Ünal KIZIL

doi:https://doi.org/10.28979/jarnas.984312

Makale detayları

Sensory Precipitation Forecast Using Artificial Neural Networks and Decision Trees

Yazarlar:

Hakkı Fırat ALTINBİLEK | Hakan NAR | Sefa AKSU | Ünal KIZIL

Yayıncı:

Çanakkale Onsekiz Mart University

Ana Başlıklar:

Tarım

Dergi:

Journal of Advanced Research in Natural and Applied Sciences 2022 Vol.8 Issue 2, pp.309-321

Belge Tipi:

Makale

Yayın Tarihi:

6/2022

Belge Dili:

İngilizce

Document ID (Org No.):

2000488237

Sıklık:

Aylık

eISSN:

2757-5195

DOI:

https://doi.org/10.28979/jarnas.984312

Özet:

 

Meteorology stations sold in the market have various difficulties in terms of their use, also these systems are costly to obtain. With state of the art sensor technologies, the development of mini weather stations has become easier. This study focuses on the development of a model weather station device using temperature, relative humidity, UV, LDR Light, rain and soil moisture sensors to collect major environmental data. The measured data were wirelessly transmitted to the remote station for logging via the GSM module and the information was sent to the database in the internet environment. In addition, the data from the sensors are organized by correlation. The classification was made according to the data obtained from the rain sensor and the relationship between the other 5 sensors used in the device to the rain classification was examined. Sensor data were scaled between 0-1 with min-max normalization before being subjected to deep learning and machine learning training. In the Decision Tree (DT) a model score of 0.96 was obtained by choosing the maximum depth of 20. The artificial neural network (ANN) yielded a classification score of 0.92 using 4 hidden layers and 100 epochs in the artificial neural network model.

Makale detayları

Sensory Precipitation Forecast Using Artificial Neural Networks and Decision Trees

Yazarlar: Hakkı Fırat ALTINBİLEK | Hakan NAR | Sefa AKSU | Ünal KIZIL

Yayıncı: Çanakkale Onsekiz Mart University

Ana Başlıklar: Tarım

Dergi: Journal of Advanced Research in Natural and Applied Sciences 2022 Vol.8 Issue 2, pp.309-321

Belge Tipi: Makale

Yayın Tarihi: 6/2022

Belge Dili: İngilizce

Document ID (Org No.): 2000488237

Sıklık: Aylık

eISSN: 2757-5195

DOI: https://doi.org/10.28979/jarnas.984312

Sayı

Yazarlar:

Hakkı Fırat ALTINBİLEK | Hakan NAR | Sefa AKSU | Ünal KIZIL

Yayıncı:

Çanakkale Onsekiz Mart University

Ana Başlıklar:

Tarım

Dergi:

Journal of Advanced Research in Natural and Applied Sciences 2022 Vol.8 Issue 2, pp.309-321

Belge Tipi:

Makale

Yayın Tarihi:

6/2022

Belge Dili:

İngilizce

Document ID (Org No.):

2000488237

Sıklık:

Aylık

eISSN:

2757-5195

DOI:

https://doi.org/10.28979/jarnas.984312