Integrating metaheuristics and ANFIS for daily mean temperature forecasting
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Tarih
2016
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Inderscience Enterprises Ltd
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
Weather forecasting is considered as a key to successful planning for various applications such as agricultural industries. Having accurate weather forecasting allows people to make better decision on managing day to day activities. Also, it has to be underlined that forecasting is important to cope with impacts of extreme events and to adapt to climatic changes. To improve weather forecasting, we used hybrid adaptive neuro-fuzzy inference system (ANFIS), which consist in exploiting capabilities of harmony search (HS) and genetic algorithm (GA), for selecting the most relevant weather variables and simultaneously searching the most appropriate structure of ANFIS. Proposed methods are applied for six different cities of Turkey which are determined according to Aydeniz's climate classification. The results of the study showed that GA-ANFIS and HS-ANFIS yield remarkable results in daily mean temperature forecasting due to the ability of capturing the advantages of both types of methods simultaneously.
Açıklama
Anahtar Kelimeler
adaptive neuro-fuzzy inference system, ANFIS, genetic algorithm, GA, harmony search, HS, daily mean temperature forecasting
Kaynak
International Journal of Global Warming
WoS Q Değeri
Q4
Scopus Q Değeri
Q3
Cilt
9
Sayı
1
