This volume constitutes the proceedings of the 10th International Conference on Simulated Evolution and Learning, SEAL 2012, held in Dunedin, New Zealand, in December 2014. The 42 full papers and 29 short papers prese...
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ISBN:
(数字)9783319135632
ISBN:
(纸本)9783319135625
This volume constitutes the proceedings of the 10th International Conference on Simulated Evolution and Learning, SEAL 2012, held in Dunedin, New Zealand, in December 2014. The 42 full papers and 29 short papers presented were carefully reviewed and selected from 109 submissions. The papers are organized in topical sections on evolutionary optimization; evolutionary multi-objective optimization; evolutionary machine learning; theoretical developments; evolutionary feature reduction; evolutionary scheduling and combinatorial optimization; real world applications and evolutionary image analysis.
Trajectory prediction is a crucial challenge in autonomous vehicle motion planning and decision-making techniques. However, existing methods face limitations in accurately capturing vehicle dynamics and interactions. ...
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Trajectory prediction is a crucial challenge in autonomous vehicle motion planning and decision-making techniques. However, existing methods face limitations in accurately capturing vehicle dynamics and interactions. To address this issue, this paper proposes a novel approach to extracting vehicle velocity and acceleration, enabling the learning of vehicle dynamics and encoding them as auxiliary information. The VDI-LSTM model is designed, incorporating graph convolution and attention mechanisms to capture vehicle interactions using trajectory data and dynamic information. Specifically, a dynamics encoder is designed to capture the dynamic information, a dynamic graph is employed to represent vehicle interactions, and an attention mechanism is introduced to enhance the performance of LSTM and graph convolution. To demonstrate the effectiveness of our model, extensive experiments are conducted, including comparisons with several baselines and ablation studies on real-world highway datasets. Experimental results show that VDI-LSTM outperforms other baselines compared, which obtains a 3% improvement on the average RMSE indicator over the five prediction steps.
This book constitutes the refereed proceedings of the First International Conference on Health Information Science, held in Beijing, China, in April 2012. The 15 full papers presented together with 1 invited pape...
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ISBN:
(数字)9783642293610
ISBN:
(纸本)9783642293603
This book constitutes the refereed proceedings of the First International Conference on Health Information Science, held in Beijing, China, in April 2012. The 15 full papers presented together with 1 invited paper and 3 industry/panel statements in this volume were carefully reviewed and selected from 38 submissions. The papers cover all aspects of the health information sciences and the systems that support this health information management and health service delivery. The scope includes 1) medical/health/biomedicine information resources, such as patient medical records, devices and equipments, software and tools to capture, store, retrieve, process, analyze, optimize the use of information in the health domain, 2) data management, data mining, and knowledge discovery (in health domain), all of which play a key role in decision making, management of public health, examination of standards, privacy and security issues, and 3) development of new architectures and applications for health information systems.
The goal of this book is to explore various security paradigms such as Machine Learning, Big data, Cyber Physical systems, and Blockchain to address both intelligence and reconfigurability in various IoT devices. The ...
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ISBN:
(数字)9783031319525
ISBN:
(纸本)9783031319518;9783031319549
The goal of this book is to explore various security paradigms such as Machine Learning, Big data, Cyber Physical systems, and Blockchain to address both intelligence and reconfigurability in various IoT devices. The book further aims to address and analyze the state of the art of blockchain-based intelligent networks in IoT systems and related technologies including healthcare sector. AI can ease, optimize, and automate the blockchain-based decision-making process for better governance and higher performance in IoT systems. Considering the incredible progress made by AI models, a blockchain system powered by intelligent AI algorithms can detect the existence of any kind of attack and automatically invoke the required defense mechanisms. In case of unavoidable damage, AI models can help to isolate the compromised component from the blockchain platform and safeguard the overall system from crashing. Furthermore, AI models can also contribute toward the robustness and scalability of blockchain-based intelligent IoT networks. The book is designed to be the first-choice reference at university libraries, academic institutions, research and development centers, information technology centers, and any institutions interested in integration of AI and IoT. The intended audience of this book include UG/PG students, Ph.D. scholars of this fields, industry technologists, young entrepreneurs, professionals, network designers, data scientists, technology specialists, practitioners, and people who are interested in exploring the role of AI and blockchain technology in IoT systems.
This book constitutes the refereed proceedings of the International Conference on the Applications of Evolutionary Computation, EvoApplications 2011, held in Torino, Italy, in April 2011 colocated with the Evo* 2011 e...
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ISBN:
(数字)9783642205200
ISBN:
(纸本)9783642205194
This book constitutes the refereed proceedings of the International Conference on the Applications of Evolutionary Computation, EvoApplications 2011, held in Torino, Italy, in April 2011 colocated with the Evo* 2011 events. Thanks to the large number of submissions received, the proceedings for EvoApplications 2011 are divided across two volumes (LNCS 6624 and 6625). The present volume contains contributions for EvoCOMNET, EvoFIN, EvoIHOT, EvoMUSART, EvoSTIM, and EvoTRANSLOC. The 51 revised full papers presented were carefully reviewed and selected from numerous submissions. This volume presents an overview about the latest research in EC. Areas where evolutionary computation techniques have been applied range from telecommunication networks to complex systems, finance and economics, games, image analysis, evolutionary music and art, parameter optimization, scheduling, and logistics. These papers may provide guidelines to help new researchers tackling their own problem using EC.
This book offers a foundational understanding of smart manufacturing (SM) and introduces effective AI methods tailored for smart manufacturing, including supervised, unsupervised, and reinforcement learning techniques...
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ISBN:
(数字)9783031801549
ISBN:
(纸本)9783031801532;9783031801563
This book offers a foundational understanding of smart manufacturing (SM) and introduces effective AI methods tailored for smart manufacturing, including supervised, unsupervised, and reinforcement learning techniques. It also features real-world industrial case studies that demonstrate the practical applications of smart manufacturing.
Drawing from the invaluable experiences gleaned from the aviation, healthcare, and semiconductors industries, this book provides an in-depth understanding of how AI is driving transformative changes in the manufacturing landscape.
In the era of rapid technological advancements, the integration of AI into manufacturing processes has emerged as a game-changer. This book serves as an indispensable guide for navigating this transformation, presenting readers with a multidimensional perspective on the diverse applications, challenges, and opportunities that AI brings to the manufacturing sector.
The book explores the emergence of Large Language Models (LLMs) as a valuable tool in manufacturing. It presents how LLMs, especially the GPT series, can process and generate textual data, offering potential applications in areas like smart manufacturing and big-data analysis. It contains detailed case studies, illustrating the practical implementation of smart manufacturing in different industries. The aviation, healthcare, automotive, and semiconductors sectors are examined, highlighting tangible benefits, challenges faced, and lessons learned from each domain.
The book addresses the future prospects of Industry 4.0 and beyond—the interconnected, data-driven evolution of manufacturing. It examines the potential impact of emerging technologies such as the Industrial Internet of Things (IIoT), 5G, and advanced robotics on the manufacturing landscape. Challenges and future possibilities pertaining to research and advancement in smart manufacturing within the domains of Aviation, Semiconductors, and Healthcare sectors are also discussed.
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