Filtreler

2012 - 20172
Filtreleri Sıfırla

Ayarlar

search.filters.applied.f.publicationcategory: Makale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı × Konu: ANN ×

Arama Sonuçları

Listeleniyor 1 - 2 / 2
  • Küçük Resim
    Öğe
    Experimental and articial neural network based studies on thermal conductivity of lightweight building materials
    (European Journal of Technique (EJT), 2017-04-01) Oktay, Hasan; Fidan, Şehmus; Sevim, Davut; Polat, Süleyman
    The growing concern about energy consumption of heating and cooling of buildings has led to a demand for improved thermal performances of building materials. In this study, an experimental investigation is performed to predict the thermal insulation properties of wall structures of which the mechanical properties are known; by using Levenberg-Marquardt training algorithm based artificial neural network (ANNs) method for energy efficient buildings. The produced samples are cement based and have relatively high insulation properties for energy efficient buildings. In this regard, 102 new concrete samples and their compositions are produced and their mechanical and thermal properties are tested in accordance with ASTM and EN standards. Then, comparisons have been made between the experimental results and the ANN predicted results. It can be concluded that thermal performance of lightweight materials could be predicted with high accuracy using artificial neural network approach.
  • Küçük Resim
    Öğe
    Calculating molding parameters in plastic injection molds with ANN and developing software
    (Taylor & Francis, 2012-02) Çelik, Yahya Hışman; Özek, Cebeli
    In recent years, plastic injection molds are widely used for producing products in various areas, such as aerospace, automotive, medical, electronics, and toys. The quality of these products depends on correctly chosen molding parameters. In this study, a new package program (NPP)-Software that calculates various injection molding parameters was developed to mold plastic products obtained by plastic injection molding techniques using the model of artificial neural network (ANN). The Delphi programming language was used in the develop the (NPP)-Software. The developed (NPP)-Software was trained and tested using the Levenberg–Marquardt (LM) algorithm, the ANN. One-thousand three-hunderd pieces of data were collected, out of which 250 were used to train the network. The ANN is employed to find optimum molding parameters that enable minimum defects in the injection-molded part, such as volumetric shrinkage, injection time, and cooling time. The three parameters predicted, using the (NPP)-Software, were compared using experimental results.