Maximum thinning rate prediction of friction heat single point incremental forming for AZ31B magnesium alloy based on BP neural network

IF 0.9 Q4 ENGINEERING, MANUFACTURING

Journal of Advanced Manufacturing Systems Pub Date : 2023-11-16 DOI:10.1142/s0219686724500197

Xu Jiang, Liuru Zhou, Panpan Li

引用次数: 0

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基于 BP 神经网络的 AZ31B 镁合金摩擦热单点增量成形最大减薄率预测

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Journal of Advanced Manufacturing Systems ENGINEERING, MANUFACTURING-

CiteScore

2.90

自引率

14.30%

发文量

期刊介绍： Journal of Advanced Manufacturing Systems publishes original papers pertaining to state-of-the-art research and development, product development, process planning, resource planning, applications, and tools in the areas related to advanced manufacturing. The journal addresses: - Manufacturing Systems - Collaborative Design - Collaborative Decision Making - Product Simulation - In-Process Modeling - Resource Planning - Resource Simulation - Tooling Design - Planning and Scheduling - Virtual Reality Technologies and Applications - CAD/CAE/CAM Systems - Networking and Distribution - Supply Chain Management