Titlebook: Computational Intelligence for Network Structure Analytics; Maoguo Gong,Qing Cai,Yu Lei Book 2017 Springer Nature Singapore Pte Ltd. 2017

bizarre

SIMUS Applied to Quantify SWOT Strategiese concepts of complex networks and the emerging topics concerning network structure analytics as well as some basic optimization models of these network structure analytics issues. Besides the addressed topics introduced in previous chapters, there are many other network structure analytics topics,

Genteel

Computational Intelligence for Network Structure Analytics

grandiose

Computational Intelligence for Network Structure Analytics978-981-10-4558-5

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Hemoptysis

Book 2017tudy such as recommender systems, system biology, etc., which will in turn expand CI’s scope and applications..As a comprehensive text, the book covers a range of key topics, including network community discovery, evolutionary optimization, network structure balance analytics, network robustness ana

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tice, addressing seminal research ideas and examining the teThis book presents the latest research advances in complex network structure analytics based on computational intelligence (CI) approaches, particularly evolutionary optimization. Most if not all network issues are actually optimization pro

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Tracheotomy

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Concluding Remarks,such as network construction, information backbone mining, structure analytics of large-scale networks, etc. These topics can also be formulated as optimization problems and may be well solved by computational intelligence methods. In this chapter, we will give several future research directions that we are working on.

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East-West Security during the 1960s and 70srks. This chapter focuses on evolutionary single-objective algorithms for solving network community discovery. First this chapter reviews evolutionary single-objective algorithm for network community discovery. Then three representative algorithms and their performances of discovering communities are introduced in detail.