Jorgie Bartelsi Permana, Muhammad Arzaki, Yanti Rusmawati
{"title":"用Prolog对金融网络级联故障进行推理","authors":"Jorgie Bartelsi Permana, Muhammad Arzaki, Yanti Rusmawati","doi":"10.1109/ICACSIS47736.2019.8979832","DOIUrl":null,"url":null,"abstract":"We construct a Prolog script that models the financial network which has the capability to simulate the spread of financial loss due to bankruptcy. Our focus is in the construction of Prolog script that simulates the cascading failure for a previously constructed model pertaining to Sariwangi AEA and Indorub bankruptcy case. The script is capable of finding bankrupt nodes, the amount of financial loss the entire model suffers, and nodes that are vulnerable to bankruptcy. A simulation is run multiple times under different financial failure threshold. From the simulation results, we obtain seven classifications regarding bankrupt nodes associated to a particular failure threshold.","PeriodicalId":165090,"journal":{"name":"2019 International Conference on Advanced Computer Science and information Systems (ICACSIS)","volume":"35 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Reasoning about the Cascading Failure of Financial Network Using Prolog\",\"authors\":\"Jorgie Bartelsi Permana, Muhammad Arzaki, Yanti Rusmawati\",\"doi\":\"10.1109/ICACSIS47736.2019.8979832\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We construct a Prolog script that models the financial network which has the capability to simulate the spread of financial loss due to bankruptcy. Our focus is in the construction of Prolog script that simulates the cascading failure for a previously constructed model pertaining to Sariwangi AEA and Indorub bankruptcy case. The script is capable of finding bankrupt nodes, the amount of financial loss the entire model suffers, and nodes that are vulnerable to bankruptcy. A simulation is run multiple times under different financial failure threshold. From the simulation results, we obtain seven classifications regarding bankrupt nodes associated to a particular failure threshold.\",\"PeriodicalId\":165090,\"journal\":{\"name\":\"2019 International Conference on Advanced Computer Science and information Systems (ICACSIS)\",\"volume\":\"35 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2019 International Conference on Advanced Computer Science and information Systems (ICACSIS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICACSIS47736.2019.8979832\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 International Conference on Advanced Computer Science and information Systems (ICACSIS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICACSIS47736.2019.8979832","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Reasoning about the Cascading Failure of Financial Network Using Prolog
We construct a Prolog script that models the financial network which has the capability to simulate the spread of financial loss due to bankruptcy. Our focus is in the construction of Prolog script that simulates the cascading failure for a previously constructed model pertaining to Sariwangi AEA and Indorub bankruptcy case. The script is capable of finding bankrupt nodes, the amount of financial loss the entire model suffers, and nodes that are vulnerable to bankruptcy. A simulation is run multiple times under different financial failure threshold. From the simulation results, we obtain seven classifications regarding bankrupt nodes associated to a particular failure threshold.