内容紹介

Networks appear everywhere in modern society, for example, power systems, communications, and infectious disease models. Thus, it is significant to analyze the characteristics of networks and behaviors of systems on the network in order to realize better society. In this presentation, I will show my previous study of the network analysis by using Boolean satisfiability (SAT) based approach, which is one of the techniques of artificial intelligence (AI). This study focuses on cascading failures on power networks. A cascading failure is a phenomenon where one failure in a system causes another and this process continues until no further failures occur. Once a cascading failure has occurred in a power system, it brings massive blackouts and huge economic and social losses. A main question to be answered in the analysis of cascading failures is which nodes are vulnerable in the sense that their failures trigger system-wide failures. The proposed approach reduces the problem of analyzing cascading failures to the SAT problem by constructing Boolean formulas that symbolically represent all possible failure scenarios under given conditions. This allows us to examine a numerous number of scenarios by means of fast modern SAT solvers which have been studied and developed in AI research fields.

詳細情報

刊年

2020

形態

電子化映像資料(42分10秒）

シリーズ名

情報科学領域・コロキアム ; 2020年度

注記

講演者所属: 情報科学領域

講演日: 2020年6月26日

講演場所:

標題言語

英語 (eng)

本文言語

英語 (eng)

著者情報

Hanada, Kenta