big data and computational intelligence in networking pdf

Big Data And Computational Intelligence In Networking Pdf

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Artificial intelligence AI is intelligence demonstrated by machines , unlike the natural intelligence displayed by humans and animals , which involves consciousness and emotionality. The distinction between the former and the latter categories is often revealed by the acronym chosen. Leading AI textbooks define the field as the study of " intelligent agents ": any device that perceives its environment and takes actions that maximize its chance of successfully achieving its goals.

Becoming Human

Artificial intelligence AI makes it possible for machines to learn from experience, adjust to new inputs and perform human-like tasks. Most AI examples that you hear about today β€” from chess-playing computers to self-driving cars β€” rely heavily on deep learning and natural language processing. Using these technologies, computers can be trained to accomplish specific tasks by processing large amounts of data and recognizing patterns in the data. The term artificial intelligence was coined in , but AI has become more popular today thanks to increased data volumes, advanced algorithms, and improvements in computing power and storage. Early AI research in the s explored topics like problem solving and symbolic methods. In the s, the US Department of Defense took interest in this type of work and began training computers to mimic basic human reasoning.

In recent years, the need for smart equipment has increased exponentially with the upsurge in technological advances. To work to their fullest capacity, these devices need to be able to communicate with other devices in their network to exchange information and receive instructions. Computational Intelligence in the Internet of Things is an essential reference source that provides relevant theoretical frameworks and the latest empirical research findings in the area of computational intelligence and the Internet of Things. Featuring research on topics such as data analytics, machine learning, and neural networks, this book is ideally designed for IT specialists, managers, professionals, researchers, and academicians. Buy Hardcover. Add to Cart.

Big Data Analytics and Artificial Intelligence in Next-Generation Wireless Networks

A vast amount of big data is opening the era of the data-driven solutions which will shape communication networks. Current networks are often designed based on the static end-to-end design principle, and their complexity has dramatically increased over the past several decades, which hinders the efficient and intelligent provision of big data. Both networking for big data and big data analytics in networking applications pose great challenges for industry and academic researchers. Small devices are continuously generating data, which are processed, cached, analyzed, and finally stored on in-network storages e. From them, users efficiently and securely discover and fetch big data for diverse purposes. Intelligent networking technologies should be designed to effectively support such big data distribution, processing, and sharing. These applications show strong demands to enable the networking decisions e.

Hybrid Computational Intelligence: Challenges and Utilities is a comprehensive resource that begins with the basics and main components of computational intelligence. It brings together many different aspects of the current research on HCI technologies, such as neural networks, support vector machines, fuzzy logic and evolutionary computation, while also covering a wide range of applications and implementation issues, from pattern recognition and system modeling, to intelligent control problems and biomedical applications. The book also explores the most widely used applications of hybrid computation as well as the history of their development. Each individual methodology provides hybrid systems with complementary reasoning and searching methods which allow the use of domain knowledge and empirical data to solve complex problems. His research interests include hybrid intelligence, pattern recognition, multimedia data processing, social networks and quantum computing.

Hybrid Computational Intelligence

It seems that you're in Germany. We have a dedicated site for Germany. This book highlights major issues related to big data analysis using computational intelligence techniques, mostly interdisciplinary in nature. It comprises chapters on computational intelligence technologies, such as neural networks and learning algorithms, evolutionary computation, fuzzy systems and other emerging techniques in data science and big data, ranging from methodologies, theory and algorithms for handling big data, to their applications in bioinformatics and related disciplines. The book describes the latest solutions, scientific results and methods in solving intriguing problems in the fields of big data analytics, intelligent agents and computational intelligence.

Computational Intelligence and Big Data Analytics

Government works Printed on acid-free paper International Standard Book Number Hardback This book contains information obtained from authentic and highly regarded sources.


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