|کد مقاله||کد نشریه||سال انتشار||مقاله انگلیسی||ترجمه فارسی||نسخه تمام متن|
|734947||1461705||2017||4 صفحه PDF||سفارش دهید||دانلود رایگان|
• Heat affected zone (HAZ) of the laser cutting process.
• HAZ forecasting based on the different laser cutting parameters.
• To analyze the influence of three inputs on the HAZ.
• To predict the HAZ.
• Extreme Learning Machine (ELM) to predict HAZ.
Heat affected zone (HAZ) of the laser cutting process may be developed based on combination of different factors. In this investigation the HAZ forecasting, based on the different laser cutting parameters, was analyzed. The main goal was to predict the HAZ according to three inputs. The purpose of this research was to develop and apply the Extreme Learning Machine (ELM) to predict the HAZ. The ELM results were compared with genetic programming (GP) and artificial neural network (ANN). The reliability of the computational models were accessed based on simulation results and by using several statistical indicators. Based upon simulation results, it was demonstrated that ELM can be utilized effectively in applications of HAZ forecasting.
Journal: Optics and Lasers in Engineering - Volume 88, January 2017, Pages 1–4