Structural Analysis of Promoter Sequences Using Grammar Inference and Support Vector Machine

Damaševičius, Robertas

doi:10.1007/978-3-540-85563-7_18

Cited by 1 publication

(1 citation statement)

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“…The optimality and the lack of transparency of AI systems or even the feasibility of their results cannot be ensured. (Hagemann et al 2019) (Damaševičius 2008) Hence, in this paper, an algorithm, which covers all of the above-listed requirements (i-v), is introduced. A discrete optimization formalization will be applied which automatically generates solutions for robotic assembly systems, specialized on the automotive body-in-white production stages.…”

Section: Literature Review and Research Gapmentioning

confidence: 99%

An optimal algorithm for the robotic assembly system design problem: An industrial case study

Hagemann

Stark

2020

CIRP Journal of Manufacturing Science and Technology

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The design process of flow-oriented assembly systems is characterized by being both highly complex and time consuming. Especially those design processes categorized into robotic and multi variant encountered in the automotive body-in-white production stages. Unlike established manual and template-based assembly system design models, which are currently applied in industry, the here presented novel approach uses a knowledge-based search algorithm and automatically generates optimal assembly system configurations. The algorithm has been implemented in a software prototype and the results have been validated against different largesize industrial scenarios in the automotive field of body-in-white production.

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Section: Literature Review and Research Gapmentioning

confidence: 99%