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In order to improve the prediction accuracy of cognitive radio spectrum and providing more reliable spectrum access for the subsequent spectrum detection, the dynamic fuzzy neural network is applied to predict the cognitive radio spectrum, and prove its feasibility. Simulation results show that the algorithm has higher accuracy than the general spectral prediction algorithm.
The rapid development of e-commerce has greatly changed the lifestyle of people. Nowadays, people are used to buying various kinds of things online, and recommender systems become more and more necessary since users are overwhelmed by a large amount of information. However, that a user's consuming behavior would change with his life stage has not been taken into consideration in most existing recommender...
Leveraging the regularities of people's trajectories, mobility prediction can help forecast social interaction opportunities. In this paper, in order to facilitate real-world social interaction, we aim to predict “serendipitous” social interactions, which are defined as unplanned encounters and interaction opportunities and regarded as emerging social interactions. We collected GPS trajectory data...
The most important challenge of the spectrum sensing in cognitive radio (CR) is to find a way to share the licensed spectrum without interfering with the licensed user transmission. Predicting the near future of the licensed or primary user (PU) channel state can solve this problem. Many studies have investigated the primary user channel state prediction in recent literature, in this study we introduce...
Predicting the licensed or primary user (PU) channel state future has been widely investigated in the recent literature, this study introduce a new approach for predicting PU channel state based on time series and hidden Markov model (HMM). In this new approach we model the primary user channel state detection sequence, which can be represented by; PU channel “idle” or “occupied” as a time series...
Smart devices, i.e., smartphone, have come into our daily lives, which become obviously inseparable. Although a variety of functions (e.g., gaming, networking, etc.) are provided, making calls remain the major task. This phenomenon implies the possibility of understanding human behaviors, especially the action contexts (e.g., moving preference, regularity, sociability, etc.), can be expected. In addition,...
Friendship prediction in social networks is useful for various applications, such as friend/place recommendation and privacy management. In this paper, we propose a friendship prediction approach by fusing the topology and geographical features in location based social networks (LBSNs). We investigate the features of users' relationship both online and offline and quantify the contributions of selected...
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