|
![]() |
|||
|
||||
OverviewThis book examines the intelligent random walk algorithms based on learning automata: these versions of random walk algorithms gradually obtain required information from the nature of the application to improve their efficiency. The book also describes the corresponding applications of this type of random walk algorithm, particularly as an efficient prediction model for large-scale networks such as peer-to-peer and social networks. The book opens new horizons for designing prediction models and problem-solving methods based on intelligent random walk algorithms, which are used for modeling and simulation in various types of networks, including computer, social and biological networks, and which may be employed a wide range of real-world applications. Full Product DetailsAuthor: Ali Mohammad Saghiri , M. Daliri Khomami , Mohammad Reza MeybodiPublisher: Springer Nature Switzerland AG Imprint: Springer Nature Switzerland AG Edition: 1st ed. 2019 Weight: 0.454kg ISBN: 9783030108823ISBN 10: 3030108821 Pages: 55 Publication Date: 14 January 2019 Audience: Professional and scholarly , Professional & Vocational Format: Paperback Publisher's Status: Active Availability: Manufactured on demand ![]() We will order this item for you from a manufactured on demand supplier. Table of ContentsRandom walk algorithms: Definitions, weaknesses, and learning automata based approach.- Intelligent Models of Random Walk.- Applications.- Conclusions.ReviewsAuthor InformationTab Content 6Author Website:Countries AvailableAll regions |