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Wyświetlanie 1-2 z 2
Tytuł:
An Expert System Coupled With a Hierarchical Structure of Fuzzy Neural Networks for Fault Diagnosis
Autorzy:
Calado, J. M. F.
Costa, I. S.
Powiązania:
https://bibliotekanauki.pl/articles/908283.pdf
Data publikacji:
1999
Wydawca:
Uniwersytet Zielonogórski. Oficyna Wydawnicza
Tematy:
rozpoznanie błędu
wykrywanie błędu
system ekspertowy
sieć neuronowa rozmyta
fault diagnosis
fault detection
fault isolation
shallow knowledge
deep knowledge
expert system
fuzzy neural network
abrupt faults
incipient faults
Opis:
An on-line fault diagnosis system, designed to be robust to the normal transient behaviour of the process, is described. The overall system consists of an expert system cascade with a hierarchical structure of fuzzy neural networks, corresponding to a multi-stage fault detection and isolation system. The fault detection is performed through the expert system by means of fault detection heuristic rules, generated from deep and shallow knowledge of the process under consideration. If a fault is detected, the hierarchical structure of fuzzy neural networks starts and it performs the fault isolation task. The structure of this diagnosis system was designed to allow for the diagnosis of single and multiple simultaneous abrupt and incipient faults from only single abrupt fault symptoms. Also, it combines the advantages of both fuzzy reasoning and neural networks learning capacity. A continuous binary distillation column has been used as a test bed of the current approach. Single, double and triple simultaneous abrupt faults, as well as incipient faults, have been considered. The preliminary results obtained show a good accuracy, even in the case of multiple faults.
Źródło:
International Journal of Applied Mathematics and Computer Science; 1999, 9, 3; 667-687
1641-876X
2083-8492
Pojawia się w:
International Journal of Applied Mathematics and Computer Science
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Knowledge, Theory and Practice in Knowledge Management: Betweeen Associative Pattering and Context-Rich Action
Autorzy:
Bennet, Alex
Bennet, David
Powiązania:
https://bibliotekanauki.pl/articles/474962.pdf
Data publikacji:
2014
Wydawca:
Fundacja Upowszechniająca Wiedzę i Naukę Cognitione
Tematy:
knowledge
knowledge management
theory
information
learning
surface knowledge
shallow knowledge
deep knowledge
neuroscience
mind/brain
decision-making
higher-order patterns
complexity
thought leaders
practitioners
knowledge (proceeding)
knowledge (informing)
SECI model
DIKW continuum
wisdom
KM research
KM frameworks
Opis:
Embedded throughout this paper you will find the diversity of opinions that correlates to the diversity of theories, frameworks, case studies and stories that are related to the field of Knowledge Management (KM). We begin by introducing the Sampler Research Call approach and the 13 KM academics and practitioners working in different parts of the world who answered the call. We then provide baseline definitions and briefly explore the process of knowledge creation within the human mind/brain. After a brief (and vastly incomplete) introduction to KM literature at the turn of the Century, the frameworks of Sampler Call participants are introduced, and two early frameworks that achieved almost cult status—the Data-Information-Knowledge-Wisdom (DIKW) continuum and the SECI (socialization, externalization, combination and internalization) model—are explored through the eyes of Sampler Call participants. We then introduce the results of the KMTL (Knowledge Management Thought Leader) Study, which suggest theories consistent with the richness and diversity of thought interwoven throughout this paper. The field of KM is introduced as a complex adaptive system with many possibilities and opportunities. Finally, we share summary thoughts, urging us as KM academics and practitioners to find the balance between the conscious awareness/understanding of higher-order patterns and the actions we take; between the need for overarching theory and the experiential freedom necessary to address context-rich situations.
Źródło:
Journal of Entrepreneurship, Management and Innovation; 2014, 10, 1; 7-55
2299-7075
2299-7326
Pojawia się w:
Journal of Entrepreneurship, Management and Innovation
Dostawca treści:
Biblioteka Nauki
Artykuł
    Wyświetlanie 1-2 z 2

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