Machines is an international, peer-reviewed, open access journal on machinery and engineering published monthly online by MDPI. The IFToMM is affiliated with Machines and its members receive a discount on the article processing charges.

About Machines Aims. Machines (ISSN 2075-1702) is an international, peer-reviewed journal on machinery and engineering. It publishes research articles, reviews and communications.

2024年12月9日 · This mechanism, combined with RNN, has shown potential in detecting short-circuit faults in synchronous machines . With the creation of multiple simultaneous attention heads and the incorporation of value encodings, the Transformer architecture emerged, which has been applied to capture multiple complex relationships in the current signals of ...

2024年11月26日 · Feature papers represent the most advanced research with significant potential for high impact in the field. A Feature Paper should be a substantial original Article that involves several techniques or approaches, provides an outlook for future research directions and describes possible research applications.

2024年12月13日 · Feature papers represent the most advanced research with significant potential for high impact in the field. A Feature Paper should be a substantial original Article that involves several techniques or approaches, provides an outlook for future research directions and describes possible research applications.

Manuscripts for Machines should be submitted online at susy.mdpi.com. The submitting author, who is generally the corresponding author, is responsible for the manuscript during the submission and peer review process.

Interests: design of high precision machines; air-bearings design; micro cutting; ultraprecision machining; smart tooling * Section: Advanced Manufacturing Special Issues, Collections and Topics in MDPI journals

2024年12月18日 · The emergence of machine learning (ML) and, more specifically, deep learning (DL) has introduced new techniques that significantly enhance prediction accuracy. ML models, such as support vector machines and ensemble models, use tabular data points to identify patterns and predict fire behavior.

2024年11月27日 · Deep learning has significantly advanced the field of natural language processing (NLP), enabling machines to understand and generate human language with high accuracy. RNNs and their variants, such as LSTMs and GRUs, have been instrumental in modeling sequential data and capturing context and dependencies in text [ 114 ].

2024年11月3日 · The size of these systems can be exceptionally large, ranging from millions to billions of degrees of freedom, and simulation times on cluster machines or supercomputers can vary from hours to days or even weeks.