Temporal knowledge representation and reasoning techniques using time Petri nets

Jong, Woei-Tzy; Shiau, Yuh-Shin; Horng, Yih-Jen; Chen, Hsin-Horng; Chen, Shyi‐Ming

doi:10.1109/3477.775271

Cited by 17 publications

(1 citation statement)

References 15 publications

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“…Liu et al [158] have proposed an adaptive fuzzy model, which can reflect the different experiences of experts and realize knowledge reasoning dynamically. Jong et al [159] have proposed temporal knowledge representation and reasoning technology. Considering heterogeneous data, Kargin et al [160] have proposed an intelligent rule engine model which realized the cognitive functions of data generalization and abstraction, while Ebrahimipour et al [161] have proposed a knowledge representation method based on ontology.…”

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confidence: 99%

The Architecture of Mass Customization-Social Internet of Things System: Current Research Profile

Dou

Sun

Wu³

et al. 2021

IJGI

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In the era of big data, mass customization (MC) systems are faced with the complexities associated with information explosion and management control. Thus, it has become necessary to integrate the mass customization system and Social Internet of Things, in order to effectively connecting customers with enterprises. We should not only allow customers to participate in MC production throughout the whole process, but also allow enterprises to control all links throughout the whole information system. To gain a better understanding, this paper first describes the architecture of the proposed system from organizational and technological perspectives. Then, based on the nature of the Social Internet of Things, the main technological application of the mass customization–Social Internet of Things (MC–SIOT) system is introduced in detail. On this basis, the key problems faced by the mass customization–Social Internet of Things system are listed. Our findings are as follows: (1) MC–SIOT can realize convenient information queries and clearly understand the user’s intentions; (2) the system can predict the changing relationships among different technical fields and help enterprise R&D personnel to find technical knowledge; and (3) it can interconnect deep learning technology and digital twin technology to better maintain the operational state of the system. However, there exist some challenges relating to data management, knowledge discovery, and human–computer interaction, such as data quality management, few data samples, a lack of dynamic learning, labor consumption, and task scheduling. Therefore, we put forward possible improvements to be assessed, as well as privacy issues and emotional interactions to be further discussed, in future research. Finally, we illustrate the behavior and evolutionary mechanism of this system, both qualitatively and quantitatively. This provides some idea of how to address the current issues pertaining to mass customization systems.

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mentioning

confidence: 99%

The Architecture of Mass Customization-Social Internet of Things System: Current Research Profile

Dou

Sun

Wu³

et al. 2021

IJGI

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Analysis of Temporal Uncertainty of Trains Converging Based on Fuzzy Time Petri Nets

Juan

Jia

2005

Fuzzy Systems and Knowledge Discovery

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Uncertain Temporal Knowledge Reasoning of Train Group Operation Based on Extended Fuzzy-Timing Petri Nets

Liu

et al.

Advances in Soft Computing

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In order to analyze quantitatively uncertain temporal knowledge in train operation, this paper proposes a temporal knowledge reasoning method, which introduces fuzzy time interval and computation of possibilities to Extended Fuzzy-Timing Petri net(EFTN) in existed train group operation Petri net models. The method can represent the temporal firing uncertainty of each enabled transition, and thus is convenient for modeling in conflict. It also provides a technique for quantitative analysis of possibilities of conflict events. The train group behaviors model shows that the method can deal with temporal uncertainty issues during the train's movement including multipath selecting in conflict, train terminal time and the possibility of train operation plan implementation, thus provides the scientific basis for the reasonable train operation plan. Compared with existed methods, this method has some outstanding characteristics such as accurate analysis, simple computation and a wide range of application.

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Temporal knowledge representation and reasoning techniques using time Petri nets

Cited by 17 publications

References 15 publications

The Architecture of Mass Customization-Social Internet of Things System: Current Research Profile

The Architecture of Mass Customization-Social Internet of Things System: Current Research Profile

Analysis of Temporal Uncertainty of Trains Converging Based on Fuzzy Time Petri Nets

Uncertain Temporal Knowledge Reasoning of Train Group Operation Based on Extended Fuzzy-Timing Petri Nets

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