The use of artificial intelligence(AI)has increased since the middle of the 20th century,as evidenced by its applications to a wide range of engineering and science problems.Air traffic management(ATM)is becoming incr...The use of artificial intelligence(AI)has increased since the middle of the 20th century,as evidenced by its applications to a wide range of engineering and science problems.Air traffic management(ATM)is becoming increasingly automated and autonomous,making it lucrative for AI applications.This paper presents a systematic review of studies that employ AI techniques for improving ATM capability.A brief account of the history,structure,and advantages of these methods is provided,followed by the description of their applications to several representative ATM tasks,such as air traffic services(ATS),airspace management(AM),air traffic flow management(ATFM),and flight operations(FO).The major contribution of the current review is the professional survey of the AI application to ATM alongside with the description of their specific advantages:(i)these methods provide alternative approaches to conventional physical modeling techniques,(ii)these methods do not require knowing relevant internal system parameters,(iii)these methods are computationally more efficient,and(iv)these methods offer compact solutions to multivariable problems.In addition,this review offers a fresh outlook on future research.One is providing a clear rationale for the model type and structure selection for a given ATM mission.Another is to understand what makes a specific architecture or algorithm effective for a given ATM mission.These are among the most important issues that will continue to attract the attention of the AI research community and ATM work teams in the future.展开更多
Cyber operations are relatively a new phenomenon of the last two decades.During that period,they have increased in number,complexity,and agility,while their design and development have been processes well kept under s...Cyber operations are relatively a new phenomenon of the last two decades.During that period,they have increased in number,complexity,and agility,while their design and development have been processes well kept under secrecy.As a consequence,limited data(sets)regarding these incidents are available.Although various academic and practitioner public communities addressed some of the key points and dilemmas that surround cyber operations(such as attack,target identification and selection,and collateral damage),still methodologies and models are needed in order to plan,execute,and assess them in a responsibly and legally compliant way.Based on these facts,it is the aim of this article to propose a model that i))estimates and classifies the effects of cyber operations,and ii)assesses proportionality in order to support targeting decisions in cyber operations.In order to do that,a multi-layered fuzzy model was designed and implemented by analysing real and virtual realistic cyber operations combined with interviews and focus groups with technical e military experts.The proposed model was evaluated on two cyber operations use cases in a focus group with four technical e military experts.Both the design and the results of the evaluation are revealed in this article.展开更多
大语言模型(large language model,LLM)及其衍生的多模态大模型因其强大的生成能力、泛化能力引发了AI新变革,但存在幻觉问题、可解释性差等不足。知识图谱(knowledge graph,KG)具备推理结果可解释、可增量知识更新等能力,但交互能力较...大语言模型(large language model,LLM)及其衍生的多模态大模型因其强大的生成能力、泛化能力引发了AI新变革,但存在幻觉问题、可解释性差等不足。知识图谱(knowledge graph,KG)具备推理结果可解释、可增量知识更新等能力,但交互能力较差。该文综述了知识图谱与大模型技术的发展历程、关键技术、优势与局限。针对电力数据与业务特点,分析了两者应用于电力领域的主流方法,建立了面向电力领域的知识图谱与大模型相融合的技术架构,重点分析了各应用场景的可行性,并指出了未来面临的挑战和可能的研究方向。展开更多
基金supported by the National Natural Science Foundation of China(62073330)the Natural Science Foundation of Hunan Province(2020JJ4339)the Scientific Research Fund of Hunan Province Education Department(20B272).
文摘The use of artificial intelligence(AI)has increased since the middle of the 20th century,as evidenced by its applications to a wide range of engineering and science problems.Air traffic management(ATM)is becoming increasingly automated and autonomous,making it lucrative for AI applications.This paper presents a systematic review of studies that employ AI techniques for improving ATM capability.A brief account of the history,structure,and advantages of these methods is provided,followed by the description of their applications to several representative ATM tasks,such as air traffic services(ATS),airspace management(AM),air traffic flow management(ATFM),and flight operations(FO).The major contribution of the current review is the professional survey of the AI application to ATM alongside with the description of their specific advantages:(i)these methods provide alternative approaches to conventional physical modeling techniques,(ii)these methods do not require knowing relevant internal system parameters,(iii)these methods are computationally more efficient,and(iv)these methods offer compact solutions to multivariable problems.In addition,this review offers a fresh outlook on future research.One is providing a clear rationale for the model type and structure selection for a given ATM mission.Another is to understand what makes a specific architecture or algorithm effective for a given ATM mission.These are among the most important issues that will continue to attract the attention of the AI research community and ATM work teams in the future.
文摘Cyber operations are relatively a new phenomenon of the last two decades.During that period,they have increased in number,complexity,and agility,while their design and development have been processes well kept under secrecy.As a consequence,limited data(sets)regarding these incidents are available.Although various academic and practitioner public communities addressed some of the key points and dilemmas that surround cyber operations(such as attack,target identification and selection,and collateral damage),still methodologies and models are needed in order to plan,execute,and assess them in a responsibly and legally compliant way.Based on these facts,it is the aim of this article to propose a model that i))estimates and classifies the effects of cyber operations,and ii)assesses proportionality in order to support targeting decisions in cyber operations.In order to do that,a multi-layered fuzzy model was designed and implemented by analysing real and virtual realistic cyber operations combined with interviews and focus groups with technical e military experts.The proposed model was evaluated on two cyber operations use cases in a focus group with four technical e military experts.Both the design and the results of the evaluation are revealed in this article.
文摘大语言模型(large language model,LLM)及其衍生的多模态大模型因其强大的生成能力、泛化能力引发了AI新变革,但存在幻觉问题、可解释性差等不足。知识图谱(knowledge graph,KG)具备推理结果可解释、可增量知识更新等能力,但交互能力较差。该文综述了知识图谱与大模型技术的发展历程、关键技术、优势与局限。针对电力数据与业务特点,分析了两者应用于电力领域的主流方法,建立了面向电力领域的知识图谱与大模型相融合的技术架构,重点分析了各应用场景的可行性,并指出了未来面临的挑战和可能的研究方向。
