{"title":"空间集体能告诉我们关于它们的环境的什么信息?","authors":"Zena Wood","doi":"10.1109/CIDM.2014.7008686","DOIUrl":null,"url":null,"abstract":"Understanding how large groups of individuals move within their environment, and the social interactions that occur during this movement, is central to many fundamental interdisciplinary research questions; ranging from understanding the evolution of cooperation, to managing human crowd behaviour. If we could understand how groups of individuals interact with their environment, and any role that the environment plays in their behaviour, we could design and develop space to better suit their needs. Spatiotemporal datasets that record the movement of large groups of individuals are becoming increasingly available. A method, based on a set of coherence criteria, has previously been developed to identify different types of collective within such datasets. However, further investigations have revealed that the method can be used to reveal important information about the environment. This paper applies the method to a spatiotemporal dataset that records the movements of ships within the Solent, in the UK, over a twenty-four hour period to explore what can be inferred from the movement of groups of individuals, referred to as spatial collectives, regarding the environment.","PeriodicalId":117542,"journal":{"name":"2014 IEEE Symposium on Computational Intelligence and Data Mining (CIDM)","volume":"259 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"What can spatial collectives tell us about their environment?\",\"authors\":\"Zena Wood\",\"doi\":\"10.1109/CIDM.2014.7008686\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Understanding how large groups of individuals move within their environment, and the social interactions that occur during this movement, is central to many fundamental interdisciplinary research questions; ranging from understanding the evolution of cooperation, to managing human crowd behaviour. If we could understand how groups of individuals interact with their environment, and any role that the environment plays in their behaviour, we could design and develop space to better suit their needs. Spatiotemporal datasets that record the movement of large groups of individuals are becoming increasingly available. A method, based on a set of coherence criteria, has previously been developed to identify different types of collective within such datasets. However, further investigations have revealed that the method can be used to reveal important information about the environment. This paper applies the method to a spatiotemporal dataset that records the movements of ships within the Solent, in the UK, over a twenty-four hour period to explore what can be inferred from the movement of groups of individuals, referred to as spatial collectives, regarding the environment.\",\"PeriodicalId\":117542,\"journal\":{\"name\":\"2014 IEEE Symposium on Computational Intelligence and Data Mining (CIDM)\",\"volume\":\"259 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2014 IEEE Symposium on Computational Intelligence and Data Mining (CIDM)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CIDM.2014.7008686\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 IEEE Symposium on Computational Intelligence and Data Mining (CIDM)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CIDM.2014.7008686","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
What can spatial collectives tell us about their environment?
Understanding how large groups of individuals move within their environment, and the social interactions that occur during this movement, is central to many fundamental interdisciplinary research questions; ranging from understanding the evolution of cooperation, to managing human crowd behaviour. If we could understand how groups of individuals interact with their environment, and any role that the environment plays in their behaviour, we could design and develop space to better suit their needs. Spatiotemporal datasets that record the movement of large groups of individuals are becoming increasingly available. A method, based on a set of coherence criteria, has previously been developed to identify different types of collective within such datasets. However, further investigations have revealed that the method can be used to reveal important information about the environment. This paper applies the method to a spatiotemporal dataset that records the movements of ships within the Solent, in the UK, over a twenty-four hour period to explore what can be inferred from the movement of groups of individuals, referred to as spatial collectives, regarding the environment.