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Found 4 papers, 1 papers with code
Time-Series Classification in Smart Manufacturing Systems: An Experimental Evaluation of State-of-the-Art Machine Learning Algorithms
The objective of this study is to fill this gap by providing a rigorous experimental evaluation of the SoTA ML and DL algorithms for TSC tasks in manufacturing and industrial settings.
Multivariate time series classification with dual attention network
DA- Net can mine essential local sequence fragments that are necessary for establishing global long-range dependencies based on the two expanded layers.
A Genetic Algorithm Meta-Heuristic for a Generalized Quadratic Assignment Problem
The GQAP addressed in this work is defined as the task of minimizing the assignment and transportation costs of assigning a set of facilities to a set of locations.
Time-Series Pattern Recognition in Smart Manufacturing Systems: A Literature Review and Ontology
Since the inception of Industry 4. 0 in 2012, emerging technologies have enabled the acquisition of vast amounts of data from diverse sources such as machine tools, robust and affordable sensor systems with advanced information models, and other sources within Smart Manufacturing Systems (SMS).
