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Titlebook: Intelligent Random Walk: An Approach Based on Learning Automata; Ali Mohammad Saghiri,M. Daliri Khomami,Mohammad Re Book 2019 The Author(s

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發(fā)表于 2025-3-21 18:42:40 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
書目名稱Intelligent Random Walk: An Approach Based on Learning Automata
編輯Ali Mohammad Saghiri,M. Daliri Khomami,Mohammad Re
視頻videohttp://file.papertrans.cn/470/469880/469880.mp4
叢書名稱SpringerBriefs in Applied Sciences and Technology
圖書封面Titlebook: Intelligent Random Walk: An Approach Based on Learning Automata;  Ali Mohammad Saghiri,M. Daliri Khomami,Mohammad Re Book 2019 The Author(s
描述.This 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..
出版日期Book 2019
關(guān)鍵詞Learning Automata; Intelligent Random Walk; Random Walk Algorithms; Learning Automaton; Artificial Intel
版次1
doihttps://doi.org/10.1007/978-3-030-10883-0
isbn_softcover978-3-030-10882-3
isbn_ebook978-3-030-10883-0Series ISSN 2191-530X Series E-ISSN 2191-5318
issn_series 2191-530X
copyrightThe Author(s), under exclusive license to Springer Nature Switzerland AG 2019
The information of publication is updating

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沙發(fā)
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發(fā)表于 2025-3-22 04:09:27 | 只看該作者
Intelligent Random Walk: An Approach Based on Learning Automata978-3-030-10883-0Series ISSN 2191-530X Series E-ISSN 2191-5318
地板
發(fā)表于 2025-3-22 06:02:26 | 只看該作者
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Random Walk Algorithms: Definitions, Weaknesses, and Learning Automata-Based Approach,e theory of learning automata is used to design intelligent models of random walk. In this chapter, we discuss about the weaknesses of non-intelligent models of random walk as a problem-solving method in real-world applications. We also give the required information about random walk algorithms and the theory of learning automata.
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發(fā)表于 2025-3-22 17:46:23 | 只看該作者
2191-530X odeling 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..978-3-030-10882-3978-3-030-10883-0Series ISSN 2191-530X Series E-ISSN 2191-5318
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發(fā)表于 2025-3-23 00:27:01 | 只看該作者
Applications, mechanism for finding a set of nodes called PIDS which leads to solve influence maximization problem. In the rest of this section, we give the required information about the selected problems, and then several solutions based on intelligent models of random walk are studied.
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發(fā)表于 2025-3-23 02:50:17 | 只看該作者
Book 2019red 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 open
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