I Gde Manik Sukanegara Adhita, Masaki Fuchi, Tsukasa Konishi, Shoji Fujimoto
{"title":"基于功能共振分析方法和动态贝叶斯网络的舰船副官性能变异性建模","authors":"I Gde Manik Sukanegara Adhita, Masaki Fuchi, Tsukasa Konishi, Shoji Fujimoto","doi":"10.12716/1001.17.04.13","DOIUrl":null,"url":null,"abstract":": Ship maneuvering is a complex operation with inherent uncertaintie s. To express this complexity in system performance during the navigation process, an analysis model has been developed using Functional Resonance Analysis Method (FRAM) and Dynamic Bayesian Network (DBN). The functional level of dynamic work onboard is assessed and modeled using FRAM qualitatively, in which a key function and the function’s potential coupling for specific instantiation are identified. Further analysis is done by integrating the FRAM analysi s with DBN for quantification. The evolution of sy stem performance over time is determined through changes in the probability of function’s mode, namely strategic, tactical opportunistic, and scrambled. The model presented in this study concerns the fluctuation of ship officer performance to overcome the obstacles during the encounter event. As a result, the integration of FRAM-DBN shows promising usability to evaluate human performance. The essence of human adaptive capacity is also highlighted through system resilience potency, that is, the potency to le arn, respond, monitor, and anticipate. We also discuss how this finding contributes to enhance safety analysis, in specific, to provide explicit representation of the dynamic in human performance in ship navigation based on Safety-II idea.","PeriodicalId":46009,"journal":{"name":"TransNav-International Journal on Marine Navigation and Safety of Sea Transportation","volume":"155 1","pages":"0"},"PeriodicalIF":0.7000,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Modelling Ship Officer Performance Variability Using Functional Resonance Analysis Method and Dynamic Bayesian Network\",\"authors\":\"I Gde Manik Sukanegara Adhita, Masaki Fuchi, Tsukasa Konishi, Shoji Fujimoto\",\"doi\":\"10.12716/1001.17.04.13\",\"DOIUrl\":null,\"url\":null,\"abstract\":\": Ship maneuvering is a complex operation with inherent uncertaintie s. To express this complexity in system performance during the navigation process, an analysis model has been developed using Functional Resonance Analysis Method (FRAM) and Dynamic Bayesian Network (DBN). The functional level of dynamic work onboard is assessed and modeled using FRAM qualitatively, in which a key function and the function’s potential coupling for specific instantiation are identified. Further analysis is done by integrating the FRAM analysi s with DBN for quantification. The evolution of sy stem performance over time is determined through changes in the probability of function’s mode, namely strategic, tactical opportunistic, and scrambled. The model presented in this study concerns the fluctuation of ship officer performance to overcome the obstacles during the encounter event. As a result, the integration of FRAM-DBN shows promising usability to evaluate human performance. The essence of human adaptive capacity is also highlighted through system resilience potency, that is, the potency to le arn, respond, monitor, and anticipate. We also discuss how this finding contributes to enhance safety analysis, in specific, to provide explicit representation of the dynamic in human performance in ship navigation based on Safety-II idea.\",\"PeriodicalId\":46009,\"journal\":{\"name\":\"TransNav-International Journal on Marine Navigation and Safety of Sea Transportation\",\"volume\":\"155 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.7000,\"publicationDate\":\"2023-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"TransNav-International Journal on Marine Navigation and Safety of Sea Transportation\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.12716/1001.17.04.13\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"TRANSPORTATION SCIENCE & TECHNOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"TransNav-International Journal on Marine Navigation and Safety of Sea Transportation","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.12716/1001.17.04.13","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"TRANSPORTATION SCIENCE & TECHNOLOGY","Score":null,"Total":0}
Modelling Ship Officer Performance Variability Using Functional Resonance Analysis Method and Dynamic Bayesian Network
: Ship maneuvering is a complex operation with inherent uncertaintie s. To express this complexity in system performance during the navigation process, an analysis model has been developed using Functional Resonance Analysis Method (FRAM) and Dynamic Bayesian Network (DBN). The functional level of dynamic work onboard is assessed and modeled using FRAM qualitatively, in which a key function and the function’s potential coupling for specific instantiation are identified. Further analysis is done by integrating the FRAM analysi s with DBN for quantification. The evolution of sy stem performance over time is determined through changes in the probability of function’s mode, namely strategic, tactical opportunistic, and scrambled. The model presented in this study concerns the fluctuation of ship officer performance to overcome the obstacles during the encounter event. As a result, the integration of FRAM-DBN shows promising usability to evaluate human performance. The essence of human adaptive capacity is also highlighted through system resilience potency, that is, the potency to le arn, respond, monitor, and anticipate. We also discuss how this finding contributes to enhance safety analysis, in specific, to provide explicit representation of the dynamic in human performance in ship navigation based on Safety-II idea.