دانلود رایگان مقاله لاتین تحلیل توزیع مسافر برای سوار شدن به هواپیما از سایت الزویر
عنوان فارسی مقاله:
مدل تجزیه و تحلیل توزیع مسافر برای زمان درک شده سوار شدن به هواپیما / سوار نشدن هواپیما، با استفاده از یک توزیع گاوسی سابق
عنوان انگلیسی مقاله:
A passenger distribution analysis model for the perceived time of airplane boarding/deboarding, utilizing an ex-Gaussian distribution
سال انتشار : 2017
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بخشی از مقاله انگلیسی:
2. Experiments
We conducted an experiment that compared perceived time with measured time, where the latter is the physical time taken to board and deboard. The experiment was conducted using tables and chairs placed in a room and were made to resemble the interior of an airplane. Participants acting as passengers were handed boarding passes and instructed to go to their allotted seats. A stopwatch was used to measure the duration from the time the first passenger entered the airplane to the time that the last passenger was seated, since this time is controllable by airline companies. A questionnaire was used to determine perceived time. The experimental conditions are summarized in Table 1. The experimental conditions of the load factor and the seat pitch differed for the low and high load factor experiments. Furthermore, two patterns were implemented for the boarding method: (1) a boarding pattern in which passengers entered the airplane in no predefined order (i.e., random boarding) regardless of the boarding passes held by them; and (2) a boarding pattern in which the seats were divided into front and back, and priority was given to passengers who were allocated seats at the back (block boarding) according to the boarding passes held by them. Two patterns were also used for deboarding: (1) a deboarding pattern in which passengers exit the airplane in no predefined order (i.e., random deboarding) regardless of the boarding passes held by them; and (2) a deboarding pattern in which deboarding started from the front (block deboarding) according to the boarding passes held by them. These boarding and deboarding patterns are shown in Fig. 1.
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