Condensation of the knowledge base in expert systems with applications to seismic risk evaluation

2010 ◽  
pp. 193-224 ◽  
Author(s):  
WEI-MIN DONG ◽  
HARESH C SHAH ◽  
FELIX S WONG
Keyword(s):  
Expert Systems ◽  
Knowledge Base ◽  
Seismic Risk ◽  
Risk Evaluation

scholarly journals Dynamic Expert System-Based Geographically Adapted Malware Risk Evaluation Method

2020 ◽  
Vol 15 (3) ◽  
Author(s):  
Donatas Vitkus ◽  
Justina Jezukevičiūtė ◽  
Nikolaj Goranin
Keyword(s):  
Risk Assessment ◽  
Expert System ◽  
Information Security ◽  
Expert Systems ◽  
Knowledge Base ◽  
Risk Evaluation ◽  
Proper Solution ◽  
Security Risk ◽  
Information Security Risk ◽  
Base Formation

Fast development of information systems and technologies while providing new opportunities for people and organizations also make them more vulnerable at the same time. Information security risk assessment helps to identify weak points and preparing mitigation actions. The analysis of expert systems has shown that rule-based expert systems are universal, and because of that can be considered as a proper solution for the task of risk assessment automation. But to assess information security risks quickly and accurately, it is necessary to process a large amount of data about newly discovered vulnerabilities or threats, to reflect regional and industry specific information, making the traditional approach of knowledge base formation for expert system problematic. This work presents a novel method for an automated expert systems knowledge base formation based on the integration of data on regional malware distribution from Cyberthreat real-time map providing current information on newly discovered threats. In our work we collect the necessary information from the web sites in an automated way, that can be later used in a relevant risk calculation. This paper presents method implementation, which includes not only knowledge base formation but also the development of the prototype of an expert system. It was created using the JESS expert system shell. Information security risk evaluation was performed according to OWASP risk assessment methodology, taking into account the location of the organization and prevalent malware in that area.

Expert systems: from database to knowledge base

1987 ◽  
Vol 29 (2) ◽  
pp. 60-65
Author(s):  
B.J. Garner
Keyword(s):  
Expert Systems ◽  
Knowledge Base

Seismic Risk Evaluation of Retrofitted Reinforced Concrete Buildings Utilizing Base Isolation and Considering Mainshock-Aftershock

2013 ◽  
Vol 671-674 ◽  
pp. 1372-1375
Author(s):  
Rui Long Han ◽  
Yue Li
Keyword(s):  
Seismic Risk ◽  
Risk Evaluation ◽  
Base Isolation ◽  
Seismic Hazards ◽  
Nonlinear Finite Element ◽  
Structural Safety ◽  
Seismic Fragility ◽  
Rc Frame ◽  
Actual Situation ◽  
Element Analysis

The insufficient consideration of seismic risk caused hidden danger for structural safety in many areas. A promising retrofit method for these structures is base isolation. In order to evaluate the effectiveness of this approach, a hypothetical RC frame based on actual situation is designed to be retrofitted using base isolation. Then, seismic fragilities for both un-retrofitted and isolated frames are analyzed, utilizing the results obtained from nonlinear finite-element analysis. The ground motion of the analysis contains 22 earthquake motions, and the results of considering mainshock-aftershock and those of considering only mainshock are compared. The study proves the well designed base isolation can reduce the seismic fragility of the RC frame effectively, and the exclusive consideration of mainshock will underestimate the seismic hazards for structures.

scholarly journals Rapid and in-depth analysis for seismic risk evaluation

2017 ◽  
Vol 909 ◽  
pp. 012071
Author(s):  
Novi Dwi Astuti ◽  
Meli Anta Alvita ◽  
Senot Sangadji ◽  
AP Rahmadi ◽  
Edy Purwanto
Keyword(s):  
Seismic Risk ◽  
Risk Evaluation ◽  
Depth Analysis

On techniques of expert systems on the example of the Akinator program

2020 ◽  
Vol 25 (2) ◽  
pp. 7-13
Author(s):  
Zhangozha A.R. ◽  
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Neural Networks ◽  
Expert Systems ◽  
Knowledge Base ◽  
Hybrid Systems ◽  
Online Game ◽  
Basic Principles ◽  
The Moment ◽  
Definition Of

On the example of the online game Akinator, the basic principles on which programs of this type are built are considered. Effective technics have been proposed by which artificial intelligence systems can build logical inferences that allow to identify an unknown subject from its description (predicate). To confirm the considered hypotheses, the terminological analysis of definition of the program "Akinator" offered by the author is carried out. Starting from the assumptions given by the author's definition, the article complements their definitions presented by other researchers and analyzes their constituent theses. Finally, some proposals are made for the next steps in improving the program. The Akinator program, at one time, became one of the most famous online games using artificial intelligence. And although this was not directly stated, it was clear to the experts in the field of artificial intelligence that the program uses the techniques of expert systems and is built on inference rules. At the moment, expert systems have lost their positions in comparison with the direction of neural networks in the field of artificial intelligence, however, in the case considered in the article, we are talking about techniques using both directions – hybrid systems. Games for filling semantics interact with the user, expanding their semantic base (knowledge base) and use certain strategies to achieve the best result. The playful form of such semantics filling programs is beneficial for researchers by involving a large number of players. The article examines the techniques used by the Akinator program, and also suggests possible modifications to it in the future. This study, first of all, focuses on how the knowledge base of the Akinator program is built, it consists of incomplete sets, which can be filled and adjusted as a result of further iterations of the program launches. It is important to note our assumption that the order of questions used by the program during the game plays a key role, because it determines its strategy. It was identified that the program is guided by the principles of nonmonotonic logic – the assumptions constructed by the program are not final and can be rejected by it during the game. The three main approaches to acquisite semantics proposed by Jakub Šimko and Mária Bieliková are considered, namely, expert work, crowdsourcing and machine learning. Paying attention to machine learning, the Akinator program using machine learning to build an effective strategy in the game presents a class of hybrid systems that combine the principles of two main areas in artificial intelligence programs – expert systems and neural networks.

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