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

Research output: Chapter in Book or Report/Conference proceedingConference Proceedingpeer-review

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 languageEnglish
Title of host publication10th International Conference on Innovations in Computer Science & Engineering (ICICSE - 2022)
Subtitle of host publicationScopus indexed LNNS Springer
PublisherSpringer
Pages369
Number of pages380
Volume565
Publication statusPublished - 1 May 2023

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