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Mikroskopinis eismo srauto modeliavimas / Microscopic traffic flow modellingJablonskytė, Janina 06 June 2006 (has links)
Everyone has had the experience of sitting in a traffic jam, or of seeing cars bunch up on a road for no apparent good reason. Nowadays the quantity of vehicles in the Lithuanian cities are growing very fast. The necessity of circumstantial territory analysis emerged for increasing Transportation Systems Control demand. Microscopic traffic flow models are important for analyzing individual crossroads and assessing interaction between some vehicles. In this paper there are analyzed microscopic traffic flow model. In this paper there answered what effect is produced by small differences in the velocities of the cars. And we have that microscopic traffic flow is in stability when kT < 0.5 and not in stability when kT > 0.5. Its very important for modeling microscopic traffic flow model. In this paper there are shown that microscopic traffic flow in K. Mindaugo – Birštono streets has Puasson distribution. There are made microscopic traffic flow simulation model of K. Mindaugo – Birštno streets crossroad by Arena 3.0 program and performed regression analysis for prognosticating microscopic traffic flow queues.
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Finansiškai stabilios bonus-malus sistemos sudarymas / Construction of financially balanced bonus-malus systemAntanaitis, Tomas 25 November 2010 (has links)
Darbe konstruojame bonus-malus sistemas, kurios yra finansiškai stabilios bėgant metams. Pasinaudodami sudėtiniu Puasono skirstiniu randame begalinės bonus-malus sistemos koeficientus. Išsprendę kvadratinio minimizavimo uždavinį randame baigtinės bonus-malus sistemos koeficientus. / Mixed Poisson fit is applied to a motor third party liability insurance portfolio in order to construct a bonus–malus system with finite number of classes. The premiums for a bonus-malus system which stays in financial equilibrium over the years are calculated. This is done by minimizing a quadratic function of the difference between the premiums for an optimal BMS with an infinite number of classes and the premiums for a BMS with finite number of classes, weighted by the stationary probability of being in a certain class, and by imposing various constraints on the system.
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