Comparison of Artificial Neural Networks and Fuzzy Logic Methods in the Hazelnut Shell Drying Process

Mert Levent; Halil Nusret Buluş; Soner Çelen; Aytaç Moralar

Makale detayları

Comparison of Artificial Neural Networks and Fuzzy Logic Methods in the Hazelnut Shell Drying Process

Yazarlar:

Mert Levent | Halil Nusret Buluş | Soner Çelen | Aytaç Moralar

Yayıncı:

Tekirdag Namik Kemal University

Ana Başlıklar:

Bilgi Modelleme | Yönetim ve Ontolojiler

Dergi:

European Journal of Engineering and Applied Sciences Vol.6 Issue 2, pp.50-55

Belge Tipi:

Makale

Yayın Tarihi:

12/2023

Belge Dili:

İngilizce

Document ID (Org No.):

2001303859

pISSN:

2651-3412

Anahtar kelimeler:

Özet:

 Drying and storing food products have been widely used techniques for extending shelf life for many years. In recent times, there has been a focus on the drying of food residues, similar to the preservation of foods by drying. The process of drying a product involves reducing the moisture content within the product. However, the devices established to reduce moisture content are often costly and rely heavily on experience-based systems for determining the drying ratio. Therefore, in recent years, there has been significant interest in the mathematical modeling of drying processes and the creation of a model for system behavior using artificial intelligence methods. This study aims to model the drying process of hazelnut shells using artificial intelligence techniques, specifically artificial neural networks and fuzzy logic methods. The proximity of the models created to the experimental results of the drying ratio is examined.

 Drying and storing food products have been widely used techniques for extending shelf life for many years. In recent times, there has been a focus on the drying of food residues, similar to the preservation of foods by drying. The process of drying a product involves reducing the moisture content within the product. However, the devices established to reduce moisture content are often costly and rely heavily on experience-based systems for determining the drying ratio. Therefore, in recent years, there has been significant interest in the mathematical modeling of drying processes and the creation of a model for system behavior using artificial intelligence methods. This study aims to model the drying process of hazelnut shells using artificial intelligence techniques, specifically artificial neural networks and fuzzy logic methods. The proximity of the models created to the experimental results of the drying ratio is examined.

 Drying and storing food products have been widely used techniques for extending shelf life for many years. In recent times, there has been a focus on the drying of food residues, similar to the preservation of foods by drying. The process of drying a product involves reducing the moisture content within the product. However, the devices established to reduce moisture content are often costly and rely heavily on experience-based systems for determining the drying ratio. Therefore, in recent years, there has been significant interest in the mathematical modeling of drying processes and the creation of a model for system behavior using artificial intelligence methods. This study aims to model the drying process of hazelnut shells using artificial intelligence techniques, specifically artificial neural networks and fuzzy logic methods. The proximity of the models created to the experimental results of the drying ratio is examined.

 Gıda ürünlerinin kurutularak saklanması kullanım ömrünü uzatması açısından uzun yıllardır kullanılan bir tekniktir. Gıdaların kurutularak saklanması gibi gıda artıklarının da kurutulması son yıllarda çalışmalara konu olmuştur. Ürün kurutma işlemi, ürün içerisindeki nem miktarının azaltılması anlamına gelmektedir. Nem miktarının azaltılması amacıyla kurulmuş olan düzenekler maliyetli ve daha çok kuruma oranının tespitinin tecrübeye dayandığı sistemlerdir. Bu sebeple son yıllarda kurutma süreçlerinin matematiksel olarak modellenmesi, yapay zeka yöntemleri ile sistem davranışının bir modelinin oluşturulması çalışmaları ilgi çekmiştir. Bu çalışmada fındık kabuğu kurutma işleminin yapay zeka tekniklerinden olan yapay sinir ağları ve bulanık mantık yöntemleri ile modellenmesi gerçekleştirilmesi hedeflenmiş ve oluşturulan modellerin kuruma oranının deneysel sonuçlarına yakınlığı incelenmiştir.

Makale detayları

Comparison of Artificial Neural Networks and Fuzzy Logic Methods in the Hazelnut Shell Drying Process

Yazarlar:

Mert Levent | Halil Nusret Buluş | Soner Çelen | Aytaç Moralar

Yayıncı:

Tekirdag Namik Kemal University

Ana Başlıklar:

Bilgi Modelleme | Yönetim ve Ontolojiler

Dergi:

European Journal of Engineering and Applied Sciences Vol.6 Issue 2, pp.50-55

Belge Tipi:

Makale

Yayın Tarihi:

12/2023

Belge Dili:

İngilizce

Document ID (Org No.):

2001303859

pISSN:

2651-3412

ANFIS

Artifical Neural Network

Drying

Fuzzy Logic

Levenberg Marquardt

PredictionANFIS

Bulanık Mantık

Kurutma

Levenberg Marquardt

Tahmin

Yapay Sinir Ağları

Sayı

Makale detayları

Yazarlar: Mert Levent | Halil Nusret Buluş | Soner Çelen | Aytaç Moralar

Yayıncı: Tekirdag Namik Kemal University

Ana Başlıklar: Bilgi Modelleme | Yönetim ve Ontolojiler

Dergi: European Journal of Engineering and Applied Sciences Vol.6 Issue 2, pp.50-55

Belge Tipi: Makale

Yayın Tarihi: 12/2023

Belge Dili: İngilizce

Document ID (Org No.): 2001303859

pISSN: 2651-3412

Sayı

Yazarlar:

Mert Levent | Halil Nusret Buluş | Soner Çelen | Aytaç Moralar

Yayıncı:

Tekirdag Namik Kemal University

Ana Başlıklar:

Bilgi Modelleme | Yönetim ve Ontolojiler

Dergi:

European Journal of Engineering and Applied Sciences Vol.6 Issue 2, pp.50-55

Belge Tipi:

Makale

Yayın Tarihi:

12/2023

Belge Dili:

İngilizce

Document ID (Org No.):

2001303859

pISSN:

2651-3412