Cargando…
Dealing with uncertainty in agent-based models for short-term predictions
Agent-based models (ABMs) are gaining traction as one of the most powerful modelling tools within the social sciences. They are particularly suited to simulating complex systems. Despite many methodological advances within ABM, one of the major drawbacks is their inability to incorporate real-time d...
Autores principales: | Kieu, Le-Minh, Malleson, Nicolas, Heppenstall, Alison |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
The Royal Society
2020
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7029931/ https://www.ncbi.nlm.nih.gov/pubmed/32218939 http://dx.doi.org/10.1098/rsos.191074 |
Ejemplares similares
-
Short-term prediction through ordinal patterns
por: Neuman, Yair, et al.
Publicado: (2021) -
Short-Term Nationwide Airport Throughput Prediction With Graph Attention Recurrent Neural Network
por: Zhu, Xinting, et al.
Publicado: (2022) -
Software defect prediction using hybrid model (CBIL) of convolutional neural network (CNN) and bidirectional long short-term memory (Bi-LSTM)
por: Farid, Ahmed Bahaa, et al.
Publicado: (2021) -
Long-short term memory networks for modeling track geometry in laser metal deposition
por: Perani, Martina, et al.
Publicado: (2023) -
A hybrid model of modal decomposition and gated recurrent units for short-term load forecasting
por: Wang, Chun-Hua, et al.
Publicado: (2023)