Competitiveness of cities, searching for a model to optimize cities
Bálint Filep, Péter Földesi, Árpád Csı́k
Abstract
Bálint Filep, Péter Földesi, Árpád Csı́k
Abstract
A larger and larger proportion of the world’s growing population lives in towns and cities. Cities can often be the places where work and related opportunities are available in concentrated forms. Besides the positive factors several negative externalities emerge. Cities are the drive of growth. The reason for this lies in the concentration of human knowledge in permanent human interaction, which is obviously concentrated in big cities and towns [1]. In our article besides the overview of the developments of cities and the connection of economic models we are looking for an answer to the questions, is it worth dealing with the optimal form of cities? And what kind of mathematical instruments can be used to sort the factors? Our hypothesis is: the problem can be modelled by fuzzy neural nets because they are able to integrate subjective and uncertain factors as well.
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A larger and larger proportion of the world’s growing population lives in towns and cities. Cities can often be the places where work and related opportunities are available in concentrated forms. Besides the positive factors several negative externalities emerge. Cities are the drive of growth. The reason for this lies in the concentration of human knowledge in permanent human interaction, which is obviously concentrated in big cities and towns [1]. In our article besides the overview of the developments of cities and the connection of economic models we are looking for an answer to the questions, is it worth dealing with the optimal form of cities? And what kind of mathematical instruments can be used to sort the factors? Our hypothesis is: the problem can be modelled by fuzzy neural nets because they are able to integrate subjective and uncertain factors as well.
Key concepts: sort, Externality, Work (physics), Population, Fuzzy logic, Economics, Economic geography, Business