This book introduces a cutting-edge hybrid modeling framework that integrates both knowledge-based and data-driven techniques to tackle the challenges faced by the simulation of intelligent combat systems. Simulation has long been the primary method for evaluating the effectiveness of combat systems, often through the creation of virtual test environments. However, the increasing complexity and dynamic nature of modern battlefield environments present significant challenges for traditional simulation modeling techniques. Combat Simulation offers readers valuable insights into the latest advancements in simulation and data engineering to overcome these challenges in the modeling of complex combat systems. Covering a wide range of topics, from ontological modeling to dynamic data modeling, this book addresses the ongoing digital transformation of combat systems. It serves as a comprehensive guide to real-world applications in the field. Intended for graduate students, researchers, and professional engineers in simulation, systems, and computer engineering, this book equips readers with the tools to teach, apply, and innovate in simulation-based defense technologies.
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Zhi Zhu is currently an Assistant Professor at the National University of Defense Technology (NUDT), Changsha, China. He received his BS degree from Sichuan University, Chengdu, China, and his MS (2013) and PhD (2018) degrees from NUDT. From 2016 to 2017, he was a visiting PhD student at Arizona State University, USA. His research interests include model-driven development and systems engineering.
Tao Wang is a Professor at the National University of Defense Technology (NUDT), Changsha, China, where he currently serves as the Director of the Department of Strategic Management Engineering in the College of Systems Engineering. He earned his BS (1998) and PhD (2007) degrees from NUDT. His research expertise lie in strategic planning, multi-agent simulation, and data mining.
Xin Zhou is currently an Associate Professor at the National University of Defense Technology (NUDT) , Changsha, China. He received his BS (2013), MS (2015) and PhD (2019) degrees from NUDT. From 2017 to 2018, he was a Visiting PhD student at the University of Adelaide, Australia. His research focuses on systems engineering, simulation modeling, and reinforcement learning.
Xiaobo Li is currently an Associate Professor at the National University of Defense Technology (NUDT) , Changsha, China. He received his BS degree from Air Force Engineering University, Xi'an, China (2005), followed by an MS degree (2007) and a PhD degree (2013) from NUDT. From 2010 to 2011, he was a visiting PhD student at the University of Antwerp, Belgium. His research centers on model-driven engineering techniques for modeling and simulation (M&S), as well as the design and evaluation of system-of-systems using simulation-based approaches.
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Hardcover. Condition: new. Hardcover. This book introduces a cutting-edge hybrid modeling framework that integrates both knowledge-based and data-driven techniques to tackle the challenges faced by the simulation of intelligent combat systems. Simulation has long been the primary method for evaluating the effectiveness of combat systems, often through the creation of virtual test environments. However, the increasing complexity and dynamic nature of modern battlefield environments present significant challenges for traditional simulation modeling techniques. Combat Simulation offers readers valuable insights into the latest advancements in simulation and data engineering to overcome these challenges in the modeling of complex combat systems. Covering a wide range of topics, from ontological modeling to dynamic data modeling, this book addresses the ongoing digital transformation of combat systems. It serves as a comprehensive guide to real-world applications in the field. Intended for graduate students, researchers, and professional engineers in simulation, systems, and computer engineering, this book equips readers with the tools to teach, apply, and innovate in simulation-based defense technologies. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Seller Inventory # 9789819822973
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