Zobrazeno 1 - 8
of 8
pro vyhledávání: '"Simon Plakolb"'
Autor:
Simon Plakolb, Nikita Strelkovskii
Publikováno v:
Systems, Vol 11, Iss 2, p 105 (2023)
Novel developments in artificial intelligence excel in regard to the abilities of rule-based agent-based models (ABMs), but are still limited in their representation of bounded rationality. The future state maximization (FSX) paradigm presents a prom
Externí odkaz:
https://doaj.org/article/def93c20bee943ef83e9e43844a20b28
Publikováno v:
MethodsX, Vol 7, Iss , Pp 100920- (2020)
We present results of attempts to expand and enhance the predictive power of Early Warning Signals (EWS) for Critical Transitions (Scheffer et al. 2009) through the deployment of a Long-Short-Term-Memory (LSTM) Neural Network on agent-based simulatio
Externí odkaz:
https://doaj.org/article/80ccd478ae6e4c17b2a6e35791048717
Publikováno v:
Atmosphere, Vol 10, Iss 6, p 293 (2019)
Motorized transport is one of the main contributors to anthropogenic CO 2 emissions, which cause global warming. Other emissions, like nitrogen oxides or carbon monoxide, are detrimental to human health. A prominent way to understand and thus be able
Externí odkaz:
https://doaj.org/article/03b576c88f61421782fd588d78918c7c
Publikováno v:
Journal of Computational Social Science. 4:163-185
We investigate the possibility to apply a method of calculus analytics developed for predicting critical transitions in complex systems to social systems modelled with agent-based methods (ABMs). We introduce this method on the example of an equation
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c12a82368f57477d11d48dba5b52866b
https://doi.org/10.1007/s42001-020-00071-y
https://doi.org/10.1007/s42001-020-00071-y
Publikováno v:
SSRN Electronic Journal.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a153c96cc1a52734f550bd9725020ba9
https://doi.org/10.2139/ssrn.4019516
https://doi.org/10.2139/ssrn.4019516
Publikováno v:
Springer Proceedings in Complexity ISBN: 9783030615024
ESSA
ESSA
Inthisstudywe investigate the different effects of urban and rural mobility behaviour on congestion and emissions. For this we use a mesoscopic hybrid agent-based network traffic model to simulate traffic in a city on a 1:1 scale. The main advantage
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::e9005659b1b75918b82c17894c29f137
https://doi.org/10.1007/978-3-030-61503-1_51
https://doi.org/10.1007/978-3-030-61503-1_51
Publikováno v:
MethodsX
MethodsX, Vol 7, Iss, Pp 100920-(2020)
MethodsX, Vol 7, Iss, Pp 100920-(2020)
We present results of attempts to expand and enhance the predictive power of Early Warning Signals (EWS) for Critical Transitions (Scheffer et al. 2009) through the deployment of a Long-Short-Term-Memory (LSTM) Neural Network on agent-based simulatio
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c63b94b2bb517eb04317387614607bcc
http://europepmc.org/articles/PMC7264060
http://europepmc.org/articles/PMC7264060
Publikováno v:
International Journal of Computational Economics and Econometrics. 11:143
We devise an algorithm that can automatically identify entry and exit nodes of an arbitrary traffic network. It is applicable even if the network is of irregular shape, which is the case for many cities. Additionally, the method can calculate the nod
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::2514ae5a3595b37241c219a8e91b9c8b
https://doi.org/10.1504/ijcee.2021.10036612
https://doi.org/10.1504/ijcee.2021.10036612