Dangerous Driving Event Analysis System by a Cascaded Fuzzy Reasoning Petri Net

The article analyzes the influence of external factors on the settlement of the situation in Syria. The author focuses on Syria's interaction with such countries as Russia, the United States, Turkey and Iran. The author provides a comparative description of the goals and objectives of these countries to resolve the situation, as well as examples of the interest of these states in resolving the conflict. Political science techniques such as event analysis, system and sociological analysis, and modeling were used in dealing with the paper topic. The author concludes that external factors in the settlement of the situation in Syria can be, both positive and negative, depending on the development of further events in the country, manifestations of opposition forces, as well as possible conflict situations between the third countries themselves.

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Reliability Analysis of Metro Door System Based on Fuzzy Reasoning Petri Net

Lecture Notes in Electrical Engineering - Proceedings of the 2013 International Conference on Electrical and Information Technologies for Rail Transportation (EITRT2013)-Volume II ◽

10.1007/978-3-642-53751-6_29 ◽

2014 ◽

pp. 283-291 ◽

Cited By ~ 1

Author(s):

Ping Liu ◽

Xiaoqing Cheng ◽

Yong Qin ◽

Yuan Zhang ◽

Zongyi Xing

Keyword(s):

Reliability Analysis ◽

Petri Net ◽

Fuzzy Reasoning

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Rough Set-Based Data Analysis in Converter Fault Diagnosis for Hybrid Power Substation

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.644-650.1136 ◽

2014 ◽

Vol 644-650 ◽

pp. 1136-1140

Author(s):

Da Jiang Ren

Keyword(s):

Data Analysis ◽

Power System ◽

Rough Set ◽

Rough Set Theory ◽

Event Analysis ◽

Acquisition Process ◽

Power Substation ◽

Concise Information ◽

Analysis System ◽

Data Analysis System

The fault in power system cannot be completely avoided. In this paper, we developed a method to resolve fault localization problems in power system. Though the data acquisition process has been highly automated, the process of assimilating and analyzing data still lags behind. Raw data must be transformed into knowledge in order to help users decide how to respond to the event and implement the necessary actions. A promising technique for substation event analysis using rough set theory is described in this paper. It interprets the data and outputs meaningful and concise information, which improves the performance of a data analysis system and help with the knowledge acquisition process. A substation model was developed to generate various fault scenarios for our case studies to evaluate the performance of the rough set algorithm. The results show that it works well and efficiently with the overwhelming data.

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Energy Saving Operation of Manufacturing System Based on Dynamic Adaptive Fuzzy Reasoning Petri Net

Energies ◽

10.3390/en12112216 ◽

2019 ◽

Vol 12 (11) ◽

pp. 2216 ◽

Cited By ~ 5

Author(s):

Junfeng Wang ◽

Zicheng Fei ◽

Qing Chang ◽

Shiqi Li

Keyword(s):

Energy Saving ◽

Real Time ◽

Petri Net ◽

Manufacturing System ◽

Fuzzy Reasoning ◽

System Level ◽

Level Energy ◽

Efficient Operation ◽

Adaptive Fuzzy ◽

Internet Of Things Technology

The energy efficient operation of a manufacturing system is important for sustainable development of industry. Apart from the device and process level, energy saving methods at the system level has attracted increasing attention with the rapid growth of the industrial Internet of things technology, which makes it possible to sense and collect real-time data from the production line and provide more opportunities for online control for energy saving purposes. In this paper, a dynamic adaptive fuzzy reasoning Petri net is proposed to decide the machine energy saving state considering the production information of a discrete stochastic manufacturing system. Fuzzy knowledge for energy saving operations of a machine is represented in weighted fuzzy production rules with certain values. The rules describe uncertain, imprecise, and ambiguous knowledge of machine state decisions. This makes an energy saving sleep decision in advance when a machine has the inclination of starvation or blockage, which is based on the real-time production rates and level of connected buffers. A dynamic adaptive fuzzy reasoning Petri net is formally defined to implement the reasoning process of the machine state decision. A manufacturing system case is used to demonstrate the application of our method and the results indicate its effectiveness for energy saving operation purposes.

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