Detecting Prosumer-Community Groups in Smart Grids From the Multiagent Perspective

Cao, Jie; Bu, Zhan; Wang, Yuyao; Yang, Huan; Jiang, Jiuchuan; Li, Hui-Jia

doi:10.1109/tsmc.2019.2899366

Cited by 145 publications

(63 citation statements)

References 26 publications

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“…The user can be subsequently analyzed by combining more attributes with the quality of the user's images. In addition, we can aggregate contributors from different locations with similar contribution behaviors to analyze the group behavior characteristics of contributors [27].…”

Section: Discussionmentioning

confidence: 99%

The State of Mapillary: An Exploratory Analysis

Fan

et al. 2019

IJGI

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As the world’s largest crowdsourcing-based street view platform, Mapillary has received considerable attention in both research and practical applications. By February 2019, more than 20,000 users worldwide contributed approximately 6.3 million kilometers of streetscape sequences. In this study, we attempted to get a deep insight into the Mapillary project through an exploratory analysis from the perspective of contributors, including the development of users, the spatiotemporal analysis of active users, the contribution modes (walking, cycling, and driving), and the devices used to contribute. It shows that inequality exists in the distribution of contributed users, similar to that in other volunteered geographic information (VGI) projects. However, the inequality in Mapillary contribution is less than in OpenStreetMap (OSM). Compared to OSM, the other main difference is that the data collection demonstrated obvious seasonal variation because contributions to OSM can be accomplished on a computer, whereas images have to be captured on the streets for Mapillary, and this is considerably affected by seasonal weather.

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Section: Discussionmentioning

confidence: 99%

The State of Mapillary: An Exploratory Analysis

Fan

et al. 2019

IJGI

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“…The research of game theory provides a novel perspective for the problems of community detection. The game theory models mainly used in this problem include non-cooperative games and cooperative games [17][18][19]. In the non-cooperative game, nodes are considered to be selfish individuals.…”

Section: Related Workmentioning

confidence: 99%

Community Detection Based on a Preferential Decision Model

et al. 2020

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The research on complex networks is a hot topic in many fields, among which community detection is a complex and meaningful process, which plays an important role in researching the characteristics of complex networks. Community structure is a common feature in the network. Given a graph, the process of uncovering its community structure is called community detection. Many community detection algorithms from different perspectives have been proposed. Achieving stable and accurate community division is still a non-trivial task due to the difficulty of setting specific parameters, high randomness and lack of ground-truth information. In this paper, we explore a new decision-making method through real-life communication and propose a preferential decision model based on dynamic relationships applied to dynamic systems. We apply this model to the label propagation algorithm and present a Community Detection based on Preferential Decision Model, called CDPD. This model intuitively aims to reveal the topological structure and the hierarchical structure between networks. By analyzing the structural characteristics of complex networks and mining the tightness between nodes, the priority of neighbor nodes is chosen to perform the required preferential decision, and finally the information in the system reaches a stable state. In the experiments, through the comparison of eight comparison algorithms, we verified the performance of CDPD in real-world networks and synthetic networks. The results show that CDPD not only has better performance than most recent algorithms on most datasets, but it is also more suitable for many community networks with ambiguous structure, especially sparse networks.

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“…At present, mathematical models have been put forward to study the role of human behavior in the context of social population, such as escape panic [19] , pedestrian trails [20] , but effort s to quantitatively explore the role of human behavior in the large-scale epidemics generally focus on assessing the effectiveness of various public health measures including the social distancing, school closure etc. In the recent years, there are many fields and methods to help us to study infectious disease [21][22][23][24][25][26][27][28][29][30][31][32] , however, there is an increasing attention about the effect of spontaneous individual action or response strategy on the progression of an infectious disease, in which this kind of spontaneous actions may highly restrain from the further diffusion of epidemics and even change the fate of outbreaks. Thus, it is of great significance to fully understand the interacting mechanisms between the human behavior and disease dynamics within the specified population.…”

Section: Introductionmentioning

confidence: 99%

Role of vaccine efficacy in the vaccination behavior under myopic update rule on complex networks

Huang

Wang

Xia

2020

Chaos, Solitons & Fractals

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a b s t r a c tHow to effectively prevent the diffusion of infectious disease has become an intriguing topic in the field of public hygienics. To be noted that, for the non-periodic infectious diseases, many people hope to obtain the vaccine of epidemics in time to be inoculated, rather than at the end of the epidemic. However, the vaccine may fail as a result of invalid storage, transportation and usage, and then vaccinated individuals may become re-susceptible and be infected again during the outbreak. To this end, we build a new framework that considers the imperfect vaccination during the one cycle of infectious disease within the spatially structured and heterogeneous population. Meanwhile, we propose a new vaccination update rule: myopic update rule, which is only based on one focal player's own perception regarding the disease outbreak, and one susceptible individual makes a decision to adopt the vaccine just by comparing the perceived payoffs vaccination with the perceived ones of being infected. Extensive Monte-Carlo simulations are performed to demonstrate the imperfect vaccination behavior under the myopic update rule in the spatially structured and heterogeneous population. The results indicate that healthy individuals are often willing to inoculate the vaccine under the myopic update rule, which can stop the infectious disease from being spread, in particular, it is found that the vaccine efficacy influences the fraction of vaccinated individuals much more than the relative cost of vaccination on the regular lattice, Meanwhile, vaccine efficacy is more sensitive on the heterogeneous scale-free network. Current results are helpful to further analyze and model the choice of vaccination strategy during the disease outbreaks.

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Detecting Prosumer-Community Groups in Smart Grids From the Multiagent Perspective

Cited by 145 publications

References 26 publications

The State of Mapillary: An Exploratory Analysis

The State of Mapillary: An Exploratory Analysis

Community Detection Based on a Preferential Decision Model

Role of vaccine efficacy in the vaccination behavior under myopic update rule on complex networks

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