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Abstract
In other growth trends and sustainable development of the economy’s globalization, low manufacturing utilization rates, production resource imbalances, and impaired coordination functions are growing. To tackle the difficulties mentioned above, organizations must securely determine how to share distant and heterogeneous production resources. Previses work is a network language learning framework for learning audio language clouds. The application offers a single computer user and Internet users economic and easy oral learning and large-scale oral assessment technologies. To select Cloud Manufacturing (CM) resources to fulfill service production enterprise assessment, five first-level metrics (time, cost, availability, reliability, security) and 13 s are used. Deep Learning (DL) is utilized to calculate the index weights, the ultimate total score, each indication, and membership at all levels. Degree determines it. It quantifies Cloud Manufacturing Resource Selection (CMRS). This model shows that manufacturing RS involves DL. Finally, it’s proven feasible to pick the resources to produce using a fuzzy comprehensive assessment
Original language | English |
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Title of host publication | 10th International Conference on Innovations in Computer Science & Engineering (ICICSE - 2022) |
Subtitle of host publication | Scopus indexed LNNS Springer |
Publisher | Springer |
Pages | 369 |
Number of pages | 380 |
Volume | 565 |
Publication status | Published - 1 May 2023 |
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Dive into the research topics of 'Evaluation and Language Training of Multinational Enterprises Employees by Deep Learning in Cloud Manufacturing Resources: https://link.springer.com/chapter/10.1007/978-981-19-7455-7_28'. Together they form a unique fingerprint.Projects
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