Významné publikační výsledky

LOM, Michal, PŘIBYL, Ondřej. Smart City Model Based on Systems Theory. International Journal of Information Management [online]. 2020. 33 s. ISSN 0268-4012. DOI: 10.1016/j.ijinfomgt.2020.102092. Dostupné také z: https://www.sciencedirect.com/science/article/pii/S0268401219301811?via%3Dihub.

While there are several partial solutions to model some aspects of cities (e.g. transportation or energy), there is no framework allowing modelling of a complex system such as a city. This paper aims on providing a solution that can be used by practitioners to model impact of different scenarios and smart city projects encapsulating different subsystems, such as transportation, energetics or, for example, eGovernment. The term “smart cities” is classified into Systems Theory, particularly focusing on Cyber-Physical Systems. This classification is further elaborated to define a new term, so-called Smart City Agent (SCA). The SCA is considered as the main building block for modelling smart cities. The approach within this paper however stresses the interconnection of different systems within a city. Its’ strength is in better exchange of data and among heterogeneous agents. This information management approach is the missing key in the growing market of partial smart city solutions as it will allow simulation of solutions in complex systems such as a city. The suitability of usefulness of the proposed approach is demonstrated on a use case dealing with charging of electrical vehicles. The results show that the approach is suitable for modelling of dynamic behaviour.

Keywords: Modelling, Multi-Agent systems, SMACEF, Smart city, Intelligent agent

JIROUŠEK, Radim, KRATOCHVÍL, Václav, RAUH, Johannes. A note on the approximation of Shenoy’s expectation operator using probabilistic transforms. International Journal of General Systems [online]. 2020, roč. 49, č. 1, s. 48–63. ISSN 0308-1079. DOI: 10.1080/03081079.2019.1692006.

Recently, a new way of computing an expected value in the Dempster–Shafer theory of evidence was introduced by Prakash P. Shenoy. Up to now, when they needed the expected value of a utility function in D-S theory, the authors usually did it indirectly: first, they found a probability measure corresponding to the considered belief function, and then computed the classical probabilistic expectation using this probability measure. To the best of our knowledge, Shenoy’s operator of expectation is the first approach that takes into account all the information included in the respective belief function. Its only drawback is its exponential computational complexity. This is why, in this paper, we compare five different approaches defining probabilistic representatives of belief function from the point of view, which of them yields the best approximations of Shenoy’s expected values of utility functions.

Keywords: Expectation, belief function, probabilistic transform, commonality function, utility, ambiguity, Choquet integral