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Titlebook: Social, Cultural, and Behavioral Modeling; 12th International C Robert Thomson,Halil Bisgin,Ayaz Hyder Conference proceedings 2019 Springer

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樓主: 哥哥大傻瓜
21#
發(fā)表于 2025-3-25 03:43:26 | 只看該作者
Dynamic Resource Allocation During Natural Disasters Using Multi-agent Environment,sually have difficulties in making optimal critical resource allocation, in this paper we introduce a novel hierarchical multi-agent reinforcement learning framework to model optimal resource allocation for natural disasters in real-time. On the lower level a set of agents navigate with the continuo
22#
發(fā)表于 2025-3-25 10:52:17 | 只看該作者
Parallelizing Convergent Cross Mapping Using Apache Spark, important but challenging in complex systems, such as those involving human behavior, sociotechnical contexts, and natural ecosystems. By exploiting state space reconstruction via lagged embedding of time series, convergent cross mapping (CCM) serves as an important method for addressing this probl
23#
發(fā)表于 2025-3-25 14:11:13 | 只看該作者
Continuous-Time Simulation of Epidemic Processes on Dynamic Interaction Networks, processes that depend upon the pattern of interactions between the individuals in the network. Continuous-time stochastic epidemic models are a natural fit for modeling the dynamics of such processes. However, prior work on such continuous-time models doesn’t consider the dynamics of the underlying
24#
發(fā)表于 2025-3-25 18:25:48 | 只看該作者
25#
發(fā)表于 2025-3-25 23:21:28 | 只看該作者
26#
發(fā)表于 2025-3-26 02:20:42 | 只看該作者
A Challenging Dataset for Bias Detection: The Case of the Crisis in the Ukraine,he Ukrainian Crisis of 2014–2015 which can be used by other researchers to train, test, and compare bias detection algorithms. The dataset comprises 4,538 articles in English related to the crisis from 227 news sources in 43 countries (including the Ukraine) comprising 1.7M words. We manually classi
27#
發(fā)表于 2025-3-26 06:17:58 | 只看該作者
28#
發(fā)表于 2025-3-26 10:31:24 | 只看該作者
Chronological Semantics Modeling: A Topic Evolution Approach in Online User-Generated Medical Data,into account language semantics as well as progression (evolution) of medical events. The preliminary evaluation on the WebMD dataset shows that evolution-based recommendation uncovers broader domain semantic which might be ignored when using word-level or concept-based features.
29#
發(fā)表于 2025-3-26 16:28:17 | 只看該作者
30#
發(fā)表于 2025-3-26 19:21:19 | 只看該作者
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