Under the background of“artificial intelligence+X”,the development of landscape architecture industry ushers in new opportunities,and professional talents need to be updated to meet the social demand.This paper anal...Under the background of“artificial intelligence+X”,the development of landscape architecture industry ushers in new opportunities,and professional talents need to be updated to meet the social demand.This paper analyzes the cultivation demand of landscape architecture graduate students in the context of the new era,and identifies the problems by comparing the original professional graduate training mode.The new cultivation mode of graduate students in landscape architecture is proposed,including updating the target orientation of the discipline,optimizing the teaching system,building a“dualteacher”tutor team,and improving the“industry-university-research-utilization”integrated cultivation,so as to cultivate high-quality compound talents with disciplinary characteristics.展开更多
With wide application prospects in landscape industry,artificial intelligence technology plays an important role in improving work efficiency,optimizing design,strengthening construction management,and achieving intel...With wide application prospects in landscape industry,artificial intelligence technology plays an important role in improving work efficiency,optimizing design,strengthening construction management,and achieving intelligent maintenance.With the continuous development of technology,the application of artificial intelligence in landscape architecture industry will become more in-depth and extensive,which can provid powerful support for the innovation and development of the industry.It is hoped that the modernization process of the landscape industry can be promoted through the analysis on the application and difficulties of artificial intelligence technology in the landscape industry.展开更多
Optical network plays an important role in telecommunication networks, which supports high-capacity and long-distance transmission of Internet traffic. However, as the scaling and evolving of optical networks, it face...Optical network plays an important role in telecommunication networks, which supports high-capacity and long-distance transmission of Internet traffic. However, as the scaling and evolving of optical networks, it faces great challenges in terms of network operation, optimization and maintenance. Artificial intelligence(AI) has been proved to have superiority on addressing complex problems, by mimicking cognitive skills similar with human mind. In this paper, we provide a comprehensive investigation of AI applications in optical transport network. First, we give a general AI-based control architecture for optical transport networks. Then, we discuss several typical applications of AI model and algorithms in optical networks. Different use cases are considered, including network planning, quality of transmission(QoT) estimation, network reconfiguration, traffic prediction, failure management and so on. In addition, we also present some potential technical challenges for AI application in optical network for the next years.展开更多
The application of the artificial intelligence(AI) technology in the 5 th generation mobile communication system(5 G) networks promotes the development of the mobile communication network and its application in vertic...The application of the artificial intelligence(AI) technology in the 5 th generation mobile communication system(5 G) networks promotes the development of the mobile communication network and its application in vertical industries, however, the application models of "patching" and "plug-in" have hindered the effect of AI applications. Meanwhile, the application of AI in all walks of life puts forward requirements for new capabilities of the future network, such as distributed training, real-time collaborative inference, local data processing, etc., which require "native intelligence design" in future networks. This paper discusses the requirements of native intelligence in the 6 th generation mobile communication system(6 G) networks from the perspectives of 5 G intelligent network challenges and the "ubiquitous intelligence" vision of 6 G, and analyzes the technical challenges of the AI workflows in its lifecycle and the AI as a service(AIaaS) in cloud network. The progress and deficiencies of the current research on AI functional architecture in various industry organizations are summarized. The end-to-end functional architecture for native AI for 6 G network and its three key technical characteristics are proposed: quality of AI services(QoAIS) based AI service orchestration for its full lifecycle, deep integration of native AI computing and communication, and integration of native AI and digital twin network. The directions of future research are also prospected.展开更多
Intelligent radio access networks(RANs)have been seen as a promising paradigm aiming to better satisfy diverse application demands and support various service scenarios.In this paper,a comprehensive survey of recent a...Intelligent radio access networks(RANs)have been seen as a promising paradigm aiming to better satisfy diverse application demands and support various service scenarios.In this paper,a comprehensive survey of recent advances in intelligent RANs is conducted.First,the efforts made by standard organizations and vendors are summarized,and several intelligent RAN architectures proposed by the academic community are presented,such as intent-driven RAN and network with enhanced data analytic.Then,several enabling techniques are introduced which include AI-driven network slicing,intent perception,intelligent operation and maintenance,AI-based cloud-edge collaborative networking,and intelligent multi-dimensional resource allocation.Furthermore,the recent progress achieved in developing experimental platforms is described.Finally,given the extensiveness of the research area,several promising future directions are outlined,in terms of standard open data sets,enabling AI with a computing power network,realization of edge intelligence,and software-defined intelligent satellite-terrestrial integrated network.展开更多
Microgrids are gaining popularity by facilitating distributed energy resources(DERs)and forming essential consumer/prosumer centric integrated energy systems.Integration,coordination and control of multiple DERs and m...Microgrids are gaining popularity by facilitating distributed energy resources(DERs)and forming essential consumer/prosumer centric integrated energy systems.Integration,coordination and control of multiple DERs and managing the energy transition in this environment is a strenuous task.Classical control techniques are not enough to support dynamic microgrid environments.Implementation of Artificial Intelligence(AI)techniques seems to be a promising solution to enhance the control and operation of microgrids in future smart grid networks.Therefore,this paper briefly reviews the control architectures,existing conventional controlling techniques,their drawbacks,the need for intelligent controllers and then extensively reviews the possibility of AI implementation in different control structures with a special focus on the hierarchical control layers.This paper also investigates the AI-based control strategies in networked/interconnected/multi-microgrids environments.It concludes with the summary and future scopes of AI implementation in hierarchical control layers and structures including single and networked microgrids environments.展开更多
基金University-level Graduate Education Reform Project of Yangtze University(YJY202329).
文摘Under the background of“artificial intelligence+X”,the development of landscape architecture industry ushers in new opportunities,and professional talents need to be updated to meet the social demand.This paper analyzes the cultivation demand of landscape architecture graduate students in the context of the new era,and identifies the problems by comparing the original professional graduate training mode.The new cultivation mode of graduate students in landscape architecture is proposed,including updating the target orientation of the discipline,optimizing the teaching system,building a“dualteacher”tutor team,and improving the“industry-university-research-utilization”integrated cultivation,so as to cultivate high-quality compound talents with disciplinary characteristics.
文摘With wide application prospects in landscape industry,artificial intelligence technology plays an important role in improving work efficiency,optimizing design,strengthening construction management,and achieving intelligent maintenance.With the continuous development of technology,the application of artificial intelligence in landscape architecture industry will become more in-depth and extensive,which can provid powerful support for the innovation and development of the industry.It is hoped that the modernization process of the landscape industry can be promoted through the analysis on the application and difficulties of artificial intelligence technology in the landscape industry.
基金supported by the National Natural Science Foundation of China(61901053,61831003,62021005)the Project of Jiangsu Engineering Research Center of Novel Optical Fiber Technologyand Communication Network,Soochow University(SDGC2117)the Fundamental Research Funds for the Central Universities(2021RC12).
文摘Optical network plays an important role in telecommunication networks, which supports high-capacity and long-distance transmission of Internet traffic. However, as the scaling and evolving of optical networks, it faces great challenges in terms of network operation, optimization and maintenance. Artificial intelligence(AI) has been proved to have superiority on addressing complex problems, by mimicking cognitive skills similar with human mind. In this paper, we provide a comprehensive investigation of AI applications in optical transport network. First, we give a general AI-based control architecture for optical transport networks. Then, we discuss several typical applications of AI model and algorithms in optical networks. Different use cases are considered, including network planning, quality of transmission(QoT) estimation, network reconfiguration, traffic prediction, failure management and so on. In addition, we also present some potential technical challenges for AI application in optical network for the next years.
基金supported by the National Key R&D Program of China (2020YFB1806800)。
文摘The application of the artificial intelligence(AI) technology in the 5 th generation mobile communication system(5 G) networks promotes the development of the mobile communication network and its application in vertical industries, however, the application models of "patching" and "plug-in" have hindered the effect of AI applications. Meanwhile, the application of AI in all walks of life puts forward requirements for new capabilities of the future network, such as distributed training, real-time collaborative inference, local data processing, etc., which require "native intelligence design" in future networks. This paper discusses the requirements of native intelligence in the 6 th generation mobile communication system(6 G) networks from the perspectives of 5 G intelligent network challenges and the "ubiquitous intelligence" vision of 6 G, and analyzes the technical challenges of the AI workflows in its lifecycle and the AI as a service(AIaaS) in cloud network. The progress and deficiencies of the current research on AI functional architecture in various industry organizations are summarized. The end-to-end functional architecture for native AI for 6 G network and its three key technical characteristics are proposed: quality of AI services(QoAIS) based AI service orchestration for its full lifecycle, deep integration of native AI computing and communication, and integration of native AI and digital twin network. The directions of future research are also prospected.
基金Project supported by the Beijing Natural Science Foundation,China(No.JQ18016)the National Natural Science Foundation of China(No.62001053)the Fundamental Research Funds for the Central Universities,China(No.24820202020RC11)。
文摘Intelligent radio access networks(RANs)have been seen as a promising paradigm aiming to better satisfy diverse application demands and support various service scenarios.In this paper,a comprehensive survey of recent advances in intelligent RANs is conducted.First,the efforts made by standard organizations and vendors are summarized,and several intelligent RAN architectures proposed by the academic community are presented,such as intent-driven RAN and network with enhanced data analytic.Then,several enabling techniques are introduced which include AI-driven network slicing,intent perception,intelligent operation and maintenance,AI-based cloud-edge collaborative networking,and intelligent multi-dimensional resource allocation.Furthermore,the recent progress achieved in developing experimental platforms is described.Finally,given the extensiveness of the research area,several promising future directions are outlined,in terms of standard open data sets,enabling AI with a computing power network,realization of edge intelligence,and software-defined intelligent satellite-terrestrial integrated network.
文摘Microgrids are gaining popularity by facilitating distributed energy resources(DERs)and forming essential consumer/prosumer centric integrated energy systems.Integration,coordination and control of multiple DERs and managing the energy transition in this environment is a strenuous task.Classical control techniques are not enough to support dynamic microgrid environments.Implementation of Artificial Intelligence(AI)techniques seems to be a promising solution to enhance the control and operation of microgrids in future smart grid networks.Therefore,this paper briefly reviews the control architectures,existing conventional controlling techniques,their drawbacks,the need for intelligent controllers and then extensively reviews the possibility of AI implementation in different control structures with a special focus on the hierarchical control layers.This paper also investigates the AI-based control strategies in networked/interconnected/multi-microgrids environments.It concludes with the summary and future scopes of AI implementation in hierarchical control layers and structures including single and networked microgrids environments.
