Discussion on The Construction Technology of Marine Environment Safety Knowledge Based on Knowledge Graphs

2020 ◽  
Author(s):  
Lie Sun ◽  
Le Wu ◽  
Fei Xu ◽  
ZhanLong Song
Keyword(s):  
Decision Making ◽  
Knowledge Representation ◽  
Knowledge Base ◽  
Emergency Response ◽  
Marine Environment ◽  
Semantic Knowledge ◽  
Construction Technology ◽  
Knowledge Graphs ◽  
Emergency Decision ◽  
Safety Knowledge

<p>The lack of the ability for machines to understand and judge semantic knowledge in the field of emergency response decision-making for marine environment safety is one of the difficulties in intelligent emergency response of marine disaster. Taking advantage of knowledge graphs in semantic search and intelligent recommendation is an important goal for the construction of the marine environment safety knowledge base. We summarizes the knowledge representation method based on knowledge graphs, analyzes the characteristics and difficulties of knowledge representation for emergency decision-making of marine environment safety, constructs the knowledge system of marine environment safety knowledge base, and proposes the construction idea of ​​marine environment safety knowledge base based on knowledge graphs.</p>

scholarly journals Hybrid Decision-making Method for Emergency Response System of Unattended Train Operation Metro

2016 ◽  
Vol 28 (2) ◽  
pp. 105-115 ◽  
Author(s):  
Bobo Zhao ◽  
Tao Tang ◽  
Bin Ning ◽  
Wei Zheng
Keyword(s):  
Decision Making ◽  
Emergency Response ◽  
Weighted Averaging ◽  
Emergency Response System ◽  
Ordered Weighted Averaging ◽  
Response System ◽  
Train Operation ◽  
Emergency Decision Making ◽  
Emergency Decision ◽  
Metro System

Suitable selection of the emergency alternatives is a critical issue in emergency response system of Unattended Train Operation (UTO) metro system of China. However, there is no available method for dispatcher group in Operating Control Center (OCC) to evaluate the decision under emergency situation. It was found that the emergency decision making in UTO metro system is relative with the preferences and the importance of multi-dispatcher in emergency. Regarding these factors, this paper presents a hybrid method to determinate the priority weights of emergency alternatives, which aggregates the preference matrix by constructing the emergency response task model based on the Weighted Ordered Weighted Averaging (WOWA) operator. This calculation approach derives the importance weights depending on the dispatcher emergency tasks and integrates it into the Ordered Weighted Averaging (OWA) operator weights based on a fuzzy membership relation. A case from train fire is given to demonstrate the feasibility and practicability of the proposed methods for Group Multi-Criteria Decision Making (GMCDM) in emergency management of UTO metro system. The innovation of this research is paving the way for a systematic emergency decision-making solution which connects the automatic metro emergency response system with the GMCDM theory.

Subway Station Group Decision and Evaluation of Fire Emergency

2014 ◽  
Vol 580-583 ◽  
pp. 1408-1411
Author(s):  
Li Jun Cao ◽  
Xiang Mei Yu ◽  
Dong Yang Geng
Keyword(s):  
Decision Making ◽  
Emergency Response ◽  
Group Decision ◽  
Subway Station ◽  
Key Factor ◽  
Emergency Group ◽  
Decision Making System ◽  
Fire Characteristics ◽  
Emergency Decision ◽  
Station Group

In order to build subway station fire emergency group decision-making system, Aim at the subway station fire characteristics in this paper, analyze the problems of emphasis from emergency decision, and group decision method is proposed to use to solve this problem. The method can avoid failure of the overall decision making mistakes because a single decision maker. Found of decision-making group consist of experts, academics, policy-makers, considering several key factor such as professional, academic, expert ratings, weight, to build group decision model .At the same time, evaluation of the subway station fire emergency group decision effectiveness to build subway station fire emergency response system, Ultimately improve the efficiency of emergency response and level of decision-making for subway station.

scholarly journals METHOD OF AUTOMATED CONSTRUCTION AND EXPANSION OF THE KNOWLEDGE BASE OF THE BUSINESS PROCESS MANAGEMENT SYSTEM

2018 ◽  
Vol 4 ◽  
pp. 29-35 ◽  
Author(s):  
Viktor Levykin ◽  
Oksana Chala
Keyword(s):  
Decision Making ◽  
Process Control ◽  
Knowledge Representation ◽  
Knowledge Base ◽  
Business Process ◽  
Business Process Management ◽  
Process Management ◽  
Process Implementation ◽  
Knowledge Intensive ◽  
Support Decision Making

The problem of constructing and using the knowledge representation in the process control system is studied. It is shown that when implementing knowledge-intensive business process management, it is necessary to use automated construction and expansion knowledge base to support decision-making in accordance with the current state of the context for the implementation of business process actions. The state of the context is specified as a set of weighted logical facts, the arguments of which are the values of the attributes of the events of the business process log. The sequence of the process implementation at each moment of time is displayed in the form of a probabilistic distribution of the possible rules of executing the actions of the business process in this context. The method of automated construction and updating of the knowledge base of the information system of process control is proposed. The method includes the stages of forming knowledge representation templates, constructing context descriptions, logical facts, constructing rules, and calculating the probability distribution for rules. The method creates opportunities to support decision-making on the management of the business process in the event of a discrepancy between the current implementation of the business process and its model.

scholarly journals Semantically Enabling Map Projections Knowledge

2020 ◽  
Vol 19 (33) ◽  
pp. 66-77
Author(s):  
E. Lynn Usery
Keyword(s):  
Decision Making ◽  
Knowledge Representation ◽  
Knowledge Base ◽  
Infinite Number ◽  
Semantic Representation ◽  
Single Equation ◽  
Use Case ◽  
Mathematical Foundation ◽  
Map Projections ◽  
Correct Orientation

Map projections are an area of cartography with a firm mathematical foundation for their creation and display providing a basis for a knowledge representation. Using only variations on a single equation set, an infinite number of projections can be created, but less than 100 are in active use. Because each projection preserves specific characteristics, such as area, angles, global look, or a compromise of properties, classifications of map projections have been developed to aid in knowledge representation. These classifications are used for decision-making. They help select the correct projection for the map use. They assist users with determining the correct orientation, standard parallels and meridians. The classifications also inform the user how to adjust the selection based on size, extent, and latitude. Semantics can be used to automate map projections knowledge into a knowledge base that can be accessed by humans and machines. This work details a semantic representation of map projections knowledge and provides a simple example of a use case that exploits the knowledge base.

EXPERT MANAGEMENT SYSTEMS OF AGROTECHNOLOGIES IN CLOUD INFORMATION TECHNOLOGY

1970 ◽  
pp. 12-17
Author(s):  
I. М. Mikhaylenko ◽  
V. N. Timoshin
Keyword(s):  
Decision Making ◽  
Pattern Recognition ◽  
Information System ◽  
Knowledge Base ◽  
Information Technologies ◽  
Agricultural Sector ◽  
Perennial Grasses ◽  
Management Decision ◽  
Agricultural Technologies ◽  
Automation Systems

The transition to "intellectual" agriculture is the main vector of modernization of the agricultural sector of the economy. It is based on integrated automation and robotization of production, the use of automated decision-making systems. This is inevitably accompanied by a significant increase in data flow from sensors, monitoring systems, meteorological stations, drones, satellites and other external systems. Farm management has the opportunity to use various online applications for accurate recommendations and making various kinds of management decisions. In this regard, the most effective use of cloud information technologies, allowing implementing the most complex information and technical level of automation systems for management of agricultural technologies. The purpose of this work is to test the approach to creating expert management decision support systems (DSS) through the knowledge base (KB), formed in the cloud information system. For this, we consider an example of constructing a DSS for choosing the optimal date for preparing forage from perennial grasses. A complete theoretical and algorithmic database of the analytical DSS implemented in the data processing center of the cloud information system is given. On its basis, a KB is formed for a variety of different decision-making conditions. This knowledge base is transmitted to the local DSS. To make decisions about the optimal dates for the preparation of the local DSS, two variants of algorithms are used. The first option is based on management models, and the second uses the pattern recognition method. The approbation of the algorithms was carried out according to the BZ from 50 cases. According to the results of testing, the method of pattern recognition proved to be more accurate, which provides a more flexible adjustment of the situation on the local DSS to a similar situation in the KB. The considered technique can be extended to other crops.

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