{"title":"Series: IEEE Press","description":"\u003cp\u003eThe \u003cstrong\u003eIEEE Press\u003c\/strong\u003e series offers a diverse selection of works spanning multiple disciplines, from cutting-edge \u003cem\u003eComputing \u0026amp; Technology\u003c\/em\u003e to insightful explorations in \u003cem\u003ePhilosophy \u0026amp; Psychology\u003c\/em\u003e and \u003cem\u003eBusiness \u0026amp; Investment\u003c\/em\u003e. Readers can expect thoughtful examinations supported by rigorous research alongside engaging narratives that challenge perspectives across various fields.\u003c\/p\u003e\n\n\u003cp\u003eThis collection also embraces a wide range of genres, including practical guides for technology certifications, historical and military studies, as well as enriching titles for younger audiences. With an emphasis on both depth and accessibility, \u003cstrong\u003eIEEE Press\u003c\/strong\u003e invites curious minds to explore topics that shape our understanding of the modern world.\u003c\/p\u003e","products":[{"product_id":"power-grid-resilience-against-natural-disasters-by-chong-wang-9781119801474","title":"Power Grid Resilience against Natural Disasters","description":"\u003cdiv class=\"book-description\"\u003e\n\u003cp\u003e\u003cem\u003ePOWER GRID RESILIENCE AGAINST NATURAL DISASTERS\u003c\/em\u003e\u003c\/p\u003e\n\n\u003cp\u003e\u003cstrong\u003eHow to protect our power grids in the face of extreme weather events\u003c\/strong\u003e\u003c\/p\u003e\n\n\u003cp\u003eThe field of structural and operational resilience of power systems, particularly against natural disasters, is of obvious importance in light of climate change and the accompanying increase in hurricanes, wildfires, tornadoes, frigid temperatures, and more. Addressing these vulnerabilities in service is a matter of increasing diligence for the electric power industry. As such, targeted studies and advanced technologies are being developed to help address these issues generally — whether they be from the threat of cyber-attacks or natural disasters.\u003c\/p\u003e\n\n\u003cp\u003e\u003cem\u003ePower Grid Resilience against Natural Disasters\u003c\/em\u003e provides, for the first time, a comprehensive and systematic introduction to resilience-enhancing planning and operation strategies of power grids against extreme events. It addresses, in detail, the three necessary steps to ensure power grid success: the preparedness prior to natural disasters, the response as natural disasters unfold, and the recovery after the event. Crucially, the authors put forward state-of-the-art methods towards improving today’s practices in managing these three arenas.\u003c\/p\u003e\n\n\u003cp\u003e\u003cem\u003ePower Grid Resilience against Natural Disasters\u003c\/em\u003e readers will also find:\u003c\/p\u003e\n\n\u003cul\u003e\n  \u003cli\u003eData, tables, and illustrations to supplement and clarify the points put forward in each chapter\u003c\/li\u003e\n  \u003cli\u003eCase studies on realistic power systems and industry standards and practices related to the topics covered\u003c\/li\u003e\n  \u003cli\u003ePotential to be a supplementary text in advanced-level power engineering courses\u003c\/li\u003e\n\u003c\/ul\u003e\n\n\u003cp\u003e\u003cem\u003ePower Grid Resilience against Natural Disasters\u003c\/em\u003e will be of interest to specialists and engineers, as well as planners and operators from industry. It can also be a useful resource for senior undergraduate students, postgraduate students, researchers, and research libraries. 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The technology development of machine learning for wireless communications has grown explosively and is one of the biggest trends in related academic, research, and industry communities.\u003c\/p\u003e\n\n\u003cp\u003eDeep neural networks-based machine learning technology is a promising tool to address the big challenges in wireless communications and networks, such as increasing demands in terms of capacity, coverage, latency, efficiency, flexibility, compatibility, quality of experience, and silicon convergence. 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