Titlebook: Learning Automata Approach for Social Networks; Alireza Rezvanian,Behnaz Moradabadi,Mohammad Reza Book 2019 Springer Nature Switzerland A

壓倒性勝利

Electrolysis

PAGAN

混亂生活

Alireza Rezvanian,Behnaz Moradabadi,Mina Ghavipour,Mohammad Mehdi Daliri Khomami,Mohammad Reza Meybo ETC) are presented along with biopsy techniques to map prostate cancer. Patient selection, treatment strategy, outcomes and safety concerns that may provide acceptable cancer control and improved quality of life for patients are all covered in detail. .?.Written by experts in the field and lavishly

斥責(zé)

Alireza Rezvanian,Behnaz Moradabadi,Mina Ghavipour,Mohammad Mehdi Daliri Khomami,Mohammad Reza Meybo ETC) are presented along with biopsy techniques to map prostate cancer. Patient selection, treatment strategy, outcomes and safety concerns that may provide acceptable cancer control and improved quality of life for patients are all covered in detail. .?.Written by experts in the field and lavishly

entitle

Alireza Rezvanian,Behnaz Moradabadi,Mina Ghavipour,Mohammad Mehdi Daliri Khomami,Mohammad Reza Meybo ETC) are presented along with biopsy techniques to map prostate cancer. Patient selection, treatment strategy, outcomes and safety concerns that may provide acceptable cancer control and improved quality of life for patients are all covered in detail. .?.Written by experts in the field and lavishly

Colonoscopy

易受刺激

明智的人

Social Trust Management,ributed learning automata for inferring trust in stochastic trust networks. Since trust changes over time as a result of repeated direct interactions between users, trust networks can be modelled as stochastic graphs with continuous time-varying edge weights. Even though the dynamic nature of trust

propose

Social Influence Maximization,he social network is maximized. In this chapter, two learning automata based approaches for influence maximization are introduced. The first one using discretized generalized confidence pursuit algorithm (DGCPA) tries to select proper seed set nodes and the second algorithm chooses heuristically see