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Wyszukujesz frazę "machine set" wg kryterium: Temat


Wyświetlanie 1-4 z 4
Tytuł:
Application of machine learning and rough set theory in lean maintenance decision support system development
Autorzy:
Antosz, Katarzyna
Jasiulewicz-Kaczmarek, Małgorzata
Paśko, Łukasz
Zhang, Chao
Wang, Shaoping
Powiązania:
https://bibliotekanauki.pl/articles/2038009.pdf
Data publikacji:
2021
Wydawca:
Polska Akademia Nauk. Polskie Naukowo-Techniczne Towarzystwo Eksploatacyjne PAN
Tematy:
lean maintenance
availability
machine learning
decision trees
rough set theory
Opis:
Lean maintenance concept is crucial to increase the reliability and availability of maintenance equipment in the manufacturing companies. Due the elimination of losses in maintenance processes this concept reduce the number of unplanned downtime and unexpected failures, simultaneously influence a company’s operational and economic performance. Despite the widespread use of lean maintenance, there is no structured approach to support the choice of methods and tools used for the maintenance function improvement. Therefore, in this paper by using machine learning methods and rough set theory a new approach was proposed. This approach supports the decision makers in the selection of methods and tools for the effective implementation of Lean Maintenance.
Źródło:
Eksploatacja i Niezawodność; 2021, 23, 4; 695-708
1507-2711
Pojawia się w:
Eksploatacja i Niezawodność
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Efficiency of the generating set with synchronous generator supplied with single-phase electricity receivers
Sprawnosc zespolu pradotworczego z synchronicznym generatorem wyposazonym w jednofazowe odbiorniki elektryczne
Autorzy:
Scibisz, M.
Makarski, P.
Powiązania:
https://bibliotekanauki.pl/articles/792172.pdf
Data publikacji:
2012
Wydawca:
Komisja Motoryzacji i Energetyki Rolnictwa
Tematy:
synchronous generating set
efficiency
generating set
synchronous machine
reactive power compensation
single-phase electricity receiver
investigation
methodology
Źródło:
Teka Komisji Motoryzacji i Energetyki Rolnictwa; 2012, 12, 2
1641-7739
Pojawia się w:
Teka Komisji Motoryzacji i Energetyki Rolnictwa
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Specialized, MSE-optimal m-estimators of the rule probability especially suitable for machine learning
Autorzy:
Piegat, A.
Landowski, M.
Powiązania:
https://bibliotekanauki.pl/articles/205508.pdf
Data publikacji:
2014
Wydawca:
Polska Akademia Nauk. Instytut Badań Systemowych PAN
Tematy:
machine learning
rule probability
probability estimation
m-estimators
decision trees
rough set theory
Opis:
The paper presents an improved sample based rule- probability estimation that is an important indicator of the rule quality and credibility in systems of machine learning. It concerns rules obtained, e.g., with the use of decision trees and rough set theory. Particular rules are frequently supported only by a small or very small number of data pieces. The rule probability is mostly investigated with the use of global estimators such as the frequency-, the Laplace-, or the m-estimator constructed for the full probability interval [0,1]. The paper shows that precision of the rule probability estimation can be considerably increased by the use of m-estimators which are specialized for the interval [phmin, phmax] given by the problem expert. The paper also presents a new interpretation of the m-estimator parameters that can be optimized in the estimators.
Źródło:
Control and Cybernetics; 2014, 43, 1; 133-160
0324-8569
Pojawia się w:
Control and Cybernetics
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Slime mould games based on rough set theory
Autorzy:
Pancerz, K.
Schumann, A.
Powiązania:
https://bibliotekanauki.pl/articles/331200.pdf
Data publikacji:
2018
Wydawca:
Uniwersytet Zielonogórski. Oficyna Wydawnicza
Tematy:
slime mould game
Physarum machine
transition system
rough set theory
simulation software
system przejściowy
teoria zbiorów przybliżonych
oprogramowanie symulacyjne
Opis:
We define games on the medium of plasmodia of slime mould, unicellular organisms that look like giant amoebae. The plasmodia try to occupy all the food pieces they can detect. Thus, two different plasmodia can compete with each other. In particular, we consider game-theoretically how plasmodia of Physarum polycephalum and Badhamia utricularis fight for food. Placing food pieces at different locations determines the behavior of plasmodia. In this way, we can program the plasmodia of Physarum polycephalum and Badhamia utricularis by placing food, and we can examine their motion as a Physarum machine—an abstract machine where states are represented as food pieces and transitions among states are represented as movements of plasmodia from one piece to another. Hence, this machine is treated as a natural transition system. The behavior of the Physarum machine in the form of a transition system can be interpreted in terms of rough set theory that enables modeling some ambiguities in motions of plasmodia. The problem is that there is always an ambiguity which direction of plasmodium propagation is currently chosen: one or several concurrent ones, i.e., whether we deal with a sequential, concurrent or massively parallel motion. We propose to manage this ambiguity using rough set theory. Firstly, we define the region of plasmodium interest as a rough set; secondly, we consider concurrent transitions determined by these regions as a context-based game; thirdly, we define strategies in this game as a rough set; fourthly, we show how these results can be interpreted as a Go game.
Źródło:
International Journal of Applied Mathematics and Computer Science; 2018, 28, 3; 531-544
1641-876X
2083-8492
Pojawia się w:
International Journal of Applied Mathematics and Computer Science
Dostawca treści:
Biblioteka Nauki
Artykuł
    Wyświetlanie 1-4 z 4

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