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In the paper different architectures with partly self-developed simulation packages are described illustrating the benefits of combining simulation and machine learning (ML) techniques in manufacturingintelligence (AI) and ML side, artificial neural networks, heuristic search, simulated annealing, and agent-based techniques are put into action.
The analysis and monitoring implementation (AMI) and Photon Science ANAlysis (psana) software packages are described.
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The development of case studies delivered in Stages 1 and 2 and utilising a number of different software packages is described.
An approach to build and analyze AND/OR graphs that makes use of hashing techniques in a way similar to that for modern Decision Diagram (DD) packages is described.
The manufacture and use of oriented films for flexible snack packaging are described.
The concept and details of implementation, user interface, and file formats of the Coarse-Graining OPTimization "CG-OPT" (version 2.0) software package are described.
The details of the implementation of the Nouna CBI scheme and its benefit package are described elsewhere [ 18- 20].
The method and its implementation in the Stata package are described further by Kim and White [ 15].
In this section, the system and organizational factors that may hinder the delivery of the ANC package are described.
Methods and functions implemented in the customProDB package are described in detail in a tutorial available as online Supplementary Material (Supplementary File 1).
This combustor and the final commercial package is described and the performance specifications discussed.
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