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Titlebook: Job-Shop-Scheduling; Planung durch probab Jukka Siedentopf Book 2002 Deutscher Universitäts-Verlag GmbH, Wiesbaden 2002 Information - Organ

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Scheduling,es Schedulings betrachtet. Von konkreten realen Kontexten, innerhalb derer Instanzen dieses Problemtyps gegebenenfalls zu lösen sind, wird dabei abstrahiert und demgegenüber angenommen, dass die betrachtete formale Spezifikation eines Problems diese Kontexte hinreichend präzise abbildet.
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https://doi.org/10.1007/978-3-322-81417-3Information - Organisation - Produktion; Kombinatorische Optimierung; Lokale Suchverfahren; Metaheurist
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978-3-8244-7611-4Deutscher Universitäts-Verlag GmbH, Wiesbaden 2002
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vantages, it has also brought the term data control to the agenda with controlling data and the ability to grow infinitely. By digitalization, the increase in online applications, which became widespread after the pandemic, both in science and in the business world, has also increased the amount of
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Jukka Siedentopf-box nature of neural models. We show that nilpotent logical systems studied in the previous chapters offer an appropriate mathematical framework for the hybridization of continuous nilpotent logic and neural models, and help improve the interpretability and safety of machine learning. In this appro
发表于 2025-3-24 16:00:33 | 显示全部楼层
Jukka Siedentopf-box nature of neural models. We show that nilpotent logical systems studied in the previous chapters offer an appropriate mathematical framework for the hybridization of continuous nilpotent logic and neural models, and help improve the interpretability and safety of machine learning. In this appro
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Jukka Siedentopfcus on nilpotent logical systems and describe aggregative operators in such systems ranging from symmetric ones (that treat all the inputs equally) to weighted ones, where some inputs are given more weight than others. As a starting point, instead of associativity, we focus on the necessary and suff
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Jukka Siedentopfth uniform weighting, and second-order with non-uniform weighting—and that they can be, respectively, mathematically modeled using classical (crisp) set theory, classical (type-1) fuzzy set theory, interval type-2 fuzzy set theory, and general type-2 fuzzy set theory; structure of a rule-based fuzzy
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