با سلام خدمت کاربران در صورتی که با خطای سیستم پرداخت بانکی مواجه شدید از طریق کارت به کارت (6037997535328901 بانک ملی ناصر خنجری ) مقاله خود را دریافت کنید (تا مشکل رفع گردد).
ردیف | عنوان | نوع |
---|---|---|
1 |
Development and application of the Activity-BAsed Traveler Analyzer (ABATA) system
توسعه و کاربرد سیستم تجزیه و تحلیل مسافرتی Activity-BAsed (ABATA)-2020 While advanced technologies and big data are widely used in the transportation study, most transportation
plans still rely on some variant of traditional four-step demand forecasting models. The most
significant limitations of the four-step model are spatiotemporal aggregation of data and difficulty of
considering individual travel behaviors. To address these drawbacks, activity-based modeling systems
have increasingly been developed. In this paper, we present a new activity-based analytical system,
called Activity-BAsed Traveler Analyzer (ABATA). The distinguishing feature of ABATA is the simulation
of the present hourly service population that is determined from mobile phone data instead of a
synthetic population. ABATA comprises multiple components, including an hourly total population
estimator, activity profile constructor, hourly activity population estimator, spatial activity population
estimator, and origin–destination estimator. To demonstrate the proposed method, a future aged
society in Gangnam, Korea is evaluated as a case study. The results indicate that the hourly activity
populations engaged in work, school, and private education decreased, while those engaged in home,
shopping, recreation and other activities increased with the aging of the population. The associated
changes in mobility were found to be rational and reasonable: older people tend to have a more flexible
working time, make shorter-distance trips, undertake more trips for shopping, recreation, home, and
other activities, and finish their trips earlier, before evening. The proposed ABATA system is expected to
provide a valuable tool for simulating the impacts of future changes in population, activity schedules,
and land use on activity populations and travel demands. Keywords: Activity-based model | Mobile phone data | Hourly service population | Mobility | Aged society |
مقاله انگلیسی |
2 |
Applying mobile phone data to travel behaviour research: A literature review
استفاده از داده های تلفن همراه برای تحقیق رفتار مسافرت: مرور ادبیاتی-2018 Travel behaviour has been studied for decades to guide transportation development and management,
with the support of traditional data collected by travel surveys. Recently, with the development of infor
mation and communication technologies (ICT), we have entered an era of big data, and many sources of
novel data, including mobile phone data, have emerged and been applied to travel behaviour research.
Compared with traditional travel data, mobile phone data have many unique features and advantages,
which attract scholars in various fields to apply them to travel behaviour research, and a certain amount
of progress has been made to date. However, this is only the beginning, and mobile phone data still have
great potential that needs to be exploited to further advance human mobility studies. This paper provides
a review of existing travel behaviour studies that have applied mobile phone data, and presents the pro
gress that has been achieved to date, and then discusses the potential of mobile phone data in advancing
travel behaviour research and raises some challenges that need to be dealt with in this process.
Keywords: Big data ، Mobile phone data ، Mobility ،Travel behaviour |
مقاله انگلیسی |
3 |
Big Data for Innovation: The Case of Credit Evaluation Using Mobile Data Analyzed by Innovation Ecosystem Lens
داده های بزرگ برای نوآوری: مورد ارزیابی اعتبار با استفاده از داده های تلفن همراه تجزیه و تحلیل شده توسط لنز اکوسیستم نوآوری-2016 Despite the high expectations about Big Data (BD) innovation potential, academy lacks studies exploring its implications and the process to achieve the announced benefits. This paper aims to help filling this gap, analyzing the case of an innovative credit assessment model, based on behavioral profiles generated over mobile network data. We ponder about the innovative potential of such huge data sets when applied to purposes differing from the ones they were generated for. To this case theoretical lens, we propose a framework where Innovation Ecosystem concepts are articulated by Contextualist elements. We explore this approach as an alternative to study the phenomenon different dimensions. It was useful to highlight that, despite the potential benefits of the solution as an enabling technology for financial inclusion and new business models in credit area, the ecosystem required for such innovation has critical dependencies delaying its progress. The study also revealed strategies used to break the inertia and create a minimum viable footprint (MVF), as a first step to chase its innovation full goals. It shows that the planning of an incremental path can be a good gimmick to deal with dependencies and enable radical change in complex ecosystems.
Keywords: Technological innovation | Technology management | Big data | Ecosystems | Lenses |
مقاله انگلیسی |