Smart cities of the future must aspire to accommodate increasing technology and expectations of modern living, integrated societies, knowledge-based workforce, factory automation, and virtual-real social behaviors. This complex concoction of challenges requires new thinking of the synergistic utilization of reinforcement learning methods and data-driven decision making with automation infrastructure, autonomous transportation, connected buildings, smart homes, and embedded communities. Industrial informatics lies at this ...
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Smart cities of the future must aspire to accommodate increasing technology and expectations of modern living, integrated societies, knowledge-based workforce, factory automation, and virtual-real social behaviors. This complex concoction of challenges requires new thinking of the synergistic utilization of reinforcement learning methods and data-driven decision making with automation infrastructure, autonomous transportation, connected buildings, smart homes, and embedded communities. Industrial informatics lies at this strategic intersection of multiple disciplines that can comprehensively realize a learning vision of smart cities. This book is ideal for academicians, researchers, authors, industry experts, software engineers, and students.
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Add this copy of Advances in Deep Learning Applications for Smart Cities to cart. $191.24, new condition, Sold by Ingram Customer Returns Center rated 5.0 out of 5 stars, ships from NV, USA, published 2022 by Engineering Science Reference.
Add this copy of Advances in Deep Learning Applications for Smart Cities to cart. $251.63, new condition, Sold by Ingram Customer Returns Center rated 5.0 out of 5 stars, ships from NV, USA, published 2022 by Business Science Reference.