Lobe Correction of a Miniaturized Microstrip Antenna Using SIW Cavity

Behera, Subhrakanta; Mohapatra, Sumant Kumar; Behera, Subhrakanta

doi:10.1007/978-981-33-4866-0_58

Cited by 1 publication

(2 citation statements)

References 8 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Since each hidden layer node represents a class (centrality), the number of nodes in the hidden layer must be greater than the number of nodes in the input layer. Different radial functions (Gaussian radial function, Thin plate spline, Quadratic, Inverse quadratic) are used as hidden layer transfer function (Behera, 2018). The most popular radial function is Gaussian radial function defined by Eq.…”

Section: Radial Basis Function (Rbf) Neural Networkmentioning

confidence: 99%

“…Therefore, any optimization method can be used for this process. Different algorithms such as Pseudo-Inverse Technique, Hybrid Learning, Levenberg-Marquardt and Gradient Descent Learning are used for the RBF network supervised learning method in the literature (Godoy et al, 2014;Behera, 2018). Gradient Descent Learning algorithm is preferred in this study.…”

Section: Radial Basis Function (Rbf) Neural Networkmentioning

confidence: 99%

See 1 more Smart Citation

Ahşap Kompozit Malzemelerin Mekanik ve Fiziksel Özelliklerine göre Tahmininde Radyal Temelli Fonksiyon Sinir Ağının Kullanımı

Kaya

Ilkuçar

Çifci

2019

Erzincan Üniversitesi Fen Bilimleri Enstitüsü Dergisi

View full text Add to dashboard Cite

Knowing the mechanical and physical properties of a material is the most important criteria for engineers and designers interested in determining the intended use of the material. The prediction of wood composite materials based on their mechanical and physical properties plays an important role in their future application. In this study, radial basis function network approach was employed for prediction according to mechanical and physical properties of wood composite materials such as particleboard, fiberboard, oriented strand board and plywood, which have widespread use in the furniture industry and construction sector. Four physical and mechanical properties were used as the board density, bending strength, bending elastic modulus and tensile strength in the prediction of the wood composite materials. This study will assist wood composite users in the selection of wood composite materials that will provide the mechanical and physical properties determined in advance for any construction. Moreover, the present study will fill this gap in literature.

show abstract

Section: Radial Basis Function (Rbf) Neural Networkmentioning

confidence: 99%

Section: Radial Basis Function (Rbf) Neural Networkmentioning

confidence: 99%