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首页> 外文期刊>International journal of uncertainty, fuzziness and knowledge-based systems >Acquiring and Sharing Tacit Knowledge Based on Interval 2-Tuple Linguistic Assessments and Extended Fuzzy Petri Nets
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Acquiring and Sharing Tacit Knowledge Based on Interval 2-Tuple Linguistic Assessments and Extended Fuzzy Petri Nets

机译：基于区间二元组语言评估和扩展模糊Petri网的隐性知识获取与共享

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摘要

In the highly competitive environment, capturing and disseminating of tacit knowledge are significant to an organization's success with the development of knowledge-based systems. However, in practical knowledge acquisition process, domain experts tend to express their judgments using multigranularity linguistic term sets, and there usually exists uncertain and incomplete information since expert knowledge is experience-based and tacit. In addition, although the technical capabilities of expert systems based on fuzzy Petri nets (FPNs) are expanding, they still fall short of meeting the increasingly complex knowledge demands. Therefore, this paper develops a theoretical model based on linguistic interval 2-tuples and interval-valued intuitionistic FPNs (IVIFPNs) for acquiring and representing tacit knowledge to increase and sustain the competitive advantages of knowledge intensive organizations. An empirical case study in medical practice is provided to demonstrate the application and feasibility of the proposed model, and the results show that it can well capture experts' tacit knowledge and reuse the acquired knowledge productively.
机译：在竞争激烈的环境中，隐性知识的获取和传播对于组织基于知识的系统的开发成功至关重要。但是，在实际的知识获取过程中，领域专家倾向于使用多粒度语言术语集来表达他们的判断力，并且由于专家知识是基于经验和默认的，因此通常存在不确定和不完整的信息。此外，尽管基于模糊Petri网（FPN）的专家系统的技术能力正在扩展，但仍不足以满足日益复杂的知识需求。因此，本文建立了基于语言区间2元组和区间值直觉FPN（IVIFPN）的理论模型，以获取和表示隐性知识，以增加和维持知识密集型组织的竞争优势。通过在医学实践中的案例研究证明了该模型的应用和可行性，结果表明该模型可以很好地捕获专家的隐性知识，并能有效地重复利用所获得的知识。

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