14871

13382

كارشناسي ارشد

ماده چگال

اصفهان : دانشگاه صنعتي اصفهان

1398

نه، 69ص.: مصور (رنگي)، جدول، نمودار

فرهاد شهبازي

مجتبي اعلايي

فرهاد فضيله، مهدي عبدي

1398/05/14

كتابنامه

فيزيك

فيزيك

1398/05/15

2551926

AbstractSyn ronization is one of the beauties of nature whi has been seen in the collective behavior of com plex physical emical and biological systems Neural networks social interactions and the Internetare examples of complex systems that coupled By looking at the overall behavior of these systems theycan be considered as graphs whi their dynamic elements are vertices of this graph and their weaklinks are graph edges One common approa to examining the syn ronization is to consider system elements as phase os cillators with a weak coupling coe cient In fact syn ronization is the tuned tra of these oscillators Along with the many models that have been presented in the past to examine this phenomenon one ofthe easiest and most comprehensive models is the Kuramoto model In most of the previous studies the rst order model was used to investigate this subject Taking intoaccount the results presented by this model the syn ronization occurs a li le faster than experimen tal observations in nature and biological samples su as re y creams e idea that completing thismodel with a damping and also inertia as a factor in anging the frequency of oscillator movement caused suggestion of second order Kuramoto model In our study a variety of complex networks has been selected that can be modeled with biological net works In this thesis we rst reviewed the previous works by applying the rst order Kuramoto modelon a variety of networks en with the use of the second order Kuramoto model we studied the im pact of damping coe cient on the syn ronization of di erent networks and nally we evaluated thesystem s state in di erent conditions Key words Syn ronization Second order Kuramoto model Phase oscillators Random network Regular network Small network Grid network

فرهاد شهبازي

مجتبي اعلايي

فرهاد فضيله، مهدي عبدي