This book emphasizes the latest developments and achievements in artificial intelligence and related technologies, focusing on the applications of artificial intelligence and medical diagnosis. The book describes the ...
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ISBN:
(数字)9783030911034
ISBN:
(纸本)9783030911027;9783030911058
This book emphasizes the latest developments and achievements in artificial intelligence and related technologies, focusing on the applications of artificial intelligence and medical diagnosis. The book describes the theory, applications, concept visualization, and critical surveys covering most aspects of AI for medical informatics.
By incorporating biologically-inspired functions into ICT, various types of new-generation information and communication systems can be created. Just some example of areas already benefiting from such design inspirati...
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ISBN:
(数字)9783642151026
ISBN:
(纸本)9783642151019;9783642266713
By incorporating biologically-inspired functions into ICT, various types of new-generation information and communication systems can be created. Just some example of areas already benefiting from such design inspiration are network architectures, information processing, molecular communication, and complex network modeling for solving real world-problems. This book provides the theoretical basis for understanding these developments and explains their practical applications. Highlighted inserts appears throughout to help readers to understand the very latest topics in these emerging research fields.
The book ends with a more philosophical discussion on how new ICT solutions can be found by looking at analogous systems in biology. This new way of thinking may help researchers and practitioners to apply innovative ideas in developing next-generation technologies.
This book provides a holistic and comprehensive approach to deep learning for vehicular ad hoc networks (VANETs), covering various aspects such as applications, agency involvement, and potential ethical and legal issu...
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ISBN:
(数字)9789819651900
ISBN:
(纸本)9789819651894;9789819651924
This book provides a holistic and comprehensive approach to deep learning for vehicular ad hoc networks (VANETs), covering various aspects such as applications, agency involvement, and potential ethical and legal issues. It begins with discussions on how the transportation system has been converted into Intelligent Transportation System (ITS). The use of VANETs is increasing in the development of ITS to enhance road safety, traffic efficiency, and driver comfort. However, the dynamic nature of vehicular environments and the high mobility of vehicles pose significant challenges to designing and implementing VANETs and ensuring reliable and efficient communication. Deep learning, a subset of machine learning, has the potential to revolutionize vehicular ad hoc networks (VANETs) to enable various applications such as traffic management, collision avoidance, and infotainment. DL has demonstrated great potential in addressing various challenges involved in VANETs by leveraging its ability to learn from vast data and make accurate predictions. It reviews the state-of-the-art DL-based approaches for various applications in VANETs, including routing, congestion control, autonomous driving, and security. In addition, this book provides a comprehensive analysis of these approaches' advantages and limitations and discusses their future research directions. The study in this book shows that DL-based techniques can significantly improve the performance and reliability of VANETs. Still, in-depth research is required to address the challenges of deploying these methods in real-world scenarios. Finally, the book discusses the potential of DL-based VANETs in supporting other emerging technologies, such as autonomous driving and smart cities. It explores the simulation/emulation tools for practical exposure to the vehicular ad hoc network.
The term “soft computing” applies to variants of and combinations under the four broad categories of evolutionary computing, neural networks, fuzzy logic, and Bayesian statistics. Although each one has its separate ...
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ISBN:
(数字)9783642045868
ISBN:
(纸本)9783642045851;9783642261503
The term “soft computing” applies to variants of and combinations under the four broad categories of evolutionary computing, neural networks, fuzzy logic, and Bayesian statistics. Although each one has its separate strengths, the complem- tary nature of these techniques when used in combination (hybrid) makes them a powerful alternative for solving complex problems where conventional mat- matical methods fail. The use of intelligent and soft computing techniques in the field of geo- chanical and pavement engineering has steadily increased over the past decade owing to their ability to admit approximate reasoning, imprecision, uncertainty and partial truth. Since real-life infrastructure engineering decisions are made in ambiguous environments that require human expertise, the application of soft computing techniques has been an attractive option in pavement and geomecha- cal modeling. The objective of this carefully edited book is to highlight key recent advances made in the application of soft computing techniques in pavement and geo- chanical systems. Soft computing techniques discussed in this book include, but are not limited to: neural networks, evolutionary computing, swarm intelligence, probabilistic modeling, kernel machines, knowledge discovery and data mining, neuro-fuzzy systems and hybrid approaches. Highlighted application areas include infrastructure materials modeling, pavement analysis and design, rapid interpre- tion of nondestructive testing results, porous asphalt concrete distress modeling, model parameter identification, pavement engineering inversion problems, s- grade soils characterization, and backcalculation of pavement layer thickness and moduli.
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