{"title":"征服排序:信息熵保持进化群体的分布特征研究","authors":"Ziyang Weng, Shuhao Wang, Jingwei Zhang","doi":"10.1109/ISSSR58837.2023.00066","DOIUrl":null,"url":null,"abstract":"In this paper, we take into account the objective evolutionary goals of different countries and regions in the course of history, combine complex military conquest with deep survival space requirements, and propose a distributional characterization algorithm for information entropy preserving evolutionary groups. We believe that firstly, we need to describe the complex evolutionary goals of individuals in the population with distributional depth; to avoid the algorithm from maturing prematurely and falling into local optimal solutions, we introduce a spatial distribution mechanism to facilitate regional development; secondly, we propose a group goal discrimination mechanism based on the population; finally, we verify the effectiveness of the algorithm using research cases. The experimental results show that the fast sorting is beneficial to the evolution of individual goals in the process of military conquest, and more beneficial to the coevolution of regional individuals. This paper can better represent the complex network of relationships between multiple intelligent nodes and provide a reference for intelligent decision making of complex systems.","PeriodicalId":185173,"journal":{"name":"2023 9th International Symposium on System Security, Safety, and Reliability (ISSSR)","volume":"181 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Conquering Sorting: A Study of the Distributional Characteristics of Information Entropy-Preserving Evolutionary Groups\",\"authors\":\"Ziyang Weng, Shuhao Wang, Jingwei Zhang\",\"doi\":\"10.1109/ISSSR58837.2023.00066\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, we take into account the objective evolutionary goals of different countries and regions in the course of history, combine complex military conquest with deep survival space requirements, and propose a distributional characterization algorithm for information entropy preserving evolutionary groups. We believe that firstly, we need to describe the complex evolutionary goals of individuals in the population with distributional depth; to avoid the algorithm from maturing prematurely and falling into local optimal solutions, we introduce a spatial distribution mechanism to facilitate regional development; secondly, we propose a group goal discrimination mechanism based on the population; finally, we verify the effectiveness of the algorithm using research cases. The experimental results show that the fast sorting is beneficial to the evolution of individual goals in the process of military conquest, and more beneficial to the coevolution of regional individuals. This paper can better represent the complex network of relationships between multiple intelligent nodes and provide a reference for intelligent decision making of complex systems.\",\"PeriodicalId\":185173,\"journal\":{\"name\":\"2023 9th International Symposium on System Security, Safety, and Reliability (ISSSR)\",\"volume\":\"181 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-06-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2023 9th International Symposium on System Security, Safety, and Reliability (ISSSR)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ISSSR58837.2023.00066\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2023 9th International Symposium on System Security, Safety, and Reliability (ISSSR)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISSSR58837.2023.00066","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Conquering Sorting: A Study of the Distributional Characteristics of Information Entropy-Preserving Evolutionary Groups
In this paper, we take into account the objective evolutionary goals of different countries and regions in the course of history, combine complex military conquest with deep survival space requirements, and propose a distributional characterization algorithm for information entropy preserving evolutionary groups. We believe that firstly, we need to describe the complex evolutionary goals of individuals in the population with distributional depth; to avoid the algorithm from maturing prematurely and falling into local optimal solutions, we introduce a spatial distribution mechanism to facilitate regional development; secondly, we propose a group goal discrimination mechanism based on the population; finally, we verify the effectiveness of the algorithm using research cases. The experimental results show that the fast sorting is beneficial to the evolution of individual goals in the process of military conquest, and more beneficial to the coevolution of regional individuals. This paper can better represent the complex network of relationships between multiple intelligent nodes and provide a reference for intelligent decision making of complex systems.