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Titlebook: Applications of Evolutionary Computation; 20th European Confer Giovanni Squillero,Kevin Sim Conference proceedings 2017 Springer Internatio

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51#
發(fā)表于 2025-3-30 12:13:56 | 只看該作者
Multi-objective Evolutionary Algorithms for Influence Maximization in Social Networksthe result. The methodology is tested on two real-world case studies, using two different influence propagation models, and compared against state-of-the-art heuristic algorithms. The results show that the proposed approach is almost always able to outperform the heuristics.
52#
發(fā)表于 2025-3-30 12:22:53 | 只看該作者
53#
發(fā)表于 2025-3-30 19:14:11 | 只看該作者
https://doi.org/10.1007/978-0-387-26336-6mechanism, where banks are connected by interbank linkages with money transfers. A mathematical model of the banking network is used to investigate the relationships between the cascade dynamics and key parameters determining the banking network structure, including the connectivity, the bank’s capi
54#
發(fā)表于 2025-3-30 21:46:40 | 只看該作者
55#
發(fā)表于 2025-3-31 04:56:26 | 只看該作者
https://doi.org/10.1007/978-0-387-26336-6istics of financial assets. It aims at providing Pareto fronts of optimal portfolios and updating them when estimated return rates or risks of financial assets change. The problem is defined in terms of dynamic optimization and solved online with a proposed evolutionary algorithm. Experiments concer
56#
發(fā)表于 2025-3-31 07:30:24 | 只看該作者
https://doi.org/10.1007/978-0-387-26336-6sed to enhance our fundamental understanding of these phenomena, as well as to optimize and engineer biological systems. An evolutionary algorithm capable of formulating mass action kinetic models of biological systems from time series data sets was developed for a system of n-species. The strategy
57#
發(fā)表于 2025-3-31 12:17:33 | 只看該作者
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