{"title":"论在 N 个不相连区域检测丢失目标的概率合作搜索模型","authors":"Mohamed Abd, Allah El-Hadidy, M. Fakharany","doi":"10.19139/soic-2310-5070-1876","DOIUrl":null,"url":null,"abstract":"This paper presents a new probabilistic coordinated search technique for finding a randomly located target in n-disjoint known regions by using n-searchers. Each region contains one searcher. The searchers use advanced technology to communicate with each other. The purpose of this paper is to obtain the candidate utility function namely the expected value of the time for detecting the target. Additionally, to minimize this expected value given a restricted amount of time. We present a special case when the target has a multinomial distribution. This important for searching about a valuable target missing at sea or lost at wilderness area.","PeriodicalId":131002,"journal":{"name":"Statistics, Optimization & Information Computing","volume":"40 9-10","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-01-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"On Probabilistic Cooperative Search Model to Detect a Lost Target in N-Disjoint Areas\",\"authors\":\"Mohamed Abd, Allah El-Hadidy, M. Fakharany\",\"doi\":\"10.19139/soic-2310-5070-1876\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper presents a new probabilistic coordinated search technique for finding a randomly located target in n-disjoint known regions by using n-searchers. Each region contains one searcher. The searchers use advanced technology to communicate with each other. The purpose of this paper is to obtain the candidate utility function namely the expected value of the time for detecting the target. Additionally, to minimize this expected value given a restricted amount of time. We present a special case when the target has a multinomial distribution. This important for searching about a valuable target missing at sea or lost at wilderness area.\",\"PeriodicalId\":131002,\"journal\":{\"name\":\"Statistics, Optimization & Information Computing\",\"volume\":\"40 9-10\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-01-17\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Statistics, Optimization & Information Computing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.19139/soic-2310-5070-1876\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Statistics, Optimization & Information Computing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.19139/soic-2310-5070-1876","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
摘要
本文提出了一种新的概率协调搜索技术,利用 n 个搜索者在 n 个不相邻的已知区域中寻找随机定位的目标。每个区域包含一名搜索者。搜索者之间使用先进技术进行通信。本文的目的是获得候选效用函数,即检测目标时间的期望值。此外,还要在时间有限的情况下最大限度地减少这一期望值。我们提出了目标具有多叉分布的一种特殊情况。这对于搜寻在海上失踪或在荒野地区丢失的有价值目标非常重要。
On Probabilistic Cooperative Search Model to Detect a Lost Target in N-Disjoint Areas
This paper presents a new probabilistic coordinated search technique for finding a randomly located target in n-disjoint known regions by using n-searchers. Each region contains one searcher. The searchers use advanced technology to communicate with each other. The purpose of this paper is to obtain the candidate utility function namely the expected value of the time for detecting the target. Additionally, to minimize this expected value given a restricted amount of time. We present a special case when the target has a multinomial distribution. This important for searching about a valuable target missing at sea or lost at wilderness area.