Perceptrons

Du, Ke-Lin; Swamy, M. N. S.

doi:10.1007/978-1-4471-5571-3_3

Cited by 1 publication

(1 citation statement)

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“…Fully Connected (FC) Layer. FC layers consist of neurons or perceptrons [65]. All neurons in a layer are connected to every other neuron in the previous layer.…”

Section: Convolution Filtersmentioning

confidence: 99%

A Survey of Machine Learning in Friction Stir Welding, including Unresolved Issues and Future Research Directions

Chadha

Selvaraj

Gunreddy

et al. 2022

Material Design & Processing Communications

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Friction stir welding is a method used to weld together materials considered challenging by fusion welding. FSW is primarily a solid phase method that has been proven efficient due to its ability to manufacture low-cost, low-distortion welds. The quality of weld and stresses can be determined by calculating the amount of heat transferred. Recently, many researchers have developed algorithms to optimize manufacturing techniques. These machine learning techniques have been applied to FSW, which allows it to predict the defect before its occurrence. ML methods such as the adaptive neurofuzzy interference system, regression model, support vector machine, and artificial neural networks were studied to predict the error percentage for the friction stir welding technique. This article examines machine learning applications in FSW by utilizing an artificial neural network (ANN) to control fracture failure and a convolutional neural network (CNN) to detect faults. The ultimate tensile strength is predicted using a regression and classification model, a decision tree model, a support vector machine for defecting classification, and Gaussian process regression (UTS). Machine learning implementation mainly promotes uniformity in the process and precision and maximally averts human error and involvement.

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“…Fully Connected (FC) Layer. FC layers consist of neurons or perceptrons [65]. All neurons in a layer are connected to every other neuron in the previous layer.…”

Section: Convolution Filtersmentioning

confidence: 99%