scholarly journals Identifying Optimum Bike Station Initial Conditions using Markov Chain Modeling

10.32866/6801 ◽  
2019 ◽  
Author(s):  
Mohammed Hamad Almannaa ◽  
Mohammed Elhenawy ◽  
Hesham A. Rakha
Keyword(s):  
Markov Chain ◽  
San Francisco ◽  
Initial Conditions ◽  
Markov Chain Model ◽  
San Francisco Bay Area ◽  
Chain Model ◽  
Initial Number ◽  
Bay Area ◽  
Bike Sharing ◽  
Typical Day

Bike sharing systems (BSSs) are being deployed in many cities because of their environmental, social, and health benefits. To maintain low rental costs, rebalancing costs must be kept minimal. In this paper, we use BSS data collected from the San Francisco Bay Area to build a Markov chain model for each bike station. The models are then used to simulate the BSS to determine the optimal station-specific initial number of bikes for a typical day to ensure that the probability of the station becoming empty or full is minimal and hence minimizing the rebalancing cost.

scholarly journals A Markov Chain Based Demand Prediction Model for Stations in Bike Sharing Systems

2018 ◽  
Vol 2018 ◽  
pp. 1-8 ◽  
Author(s):  
Yajun Zhou ◽  
Lilei Wang ◽  
Rong Zhong ◽  
Yulong Tan
Keyword(s):  
Markov Chain ◽  
Markov Chain Model ◽  
Prediction Method ◽  
Chain Model ◽  
Daily Production ◽  
Forecasting Accuracy ◽  
Traffic Demand ◽  
Demand Prediction ◽  
Proposed Model ◽  
Bike Sharing

Accurate transfer demand prediction at bike stations is the key to develop balancing solutions to address the overutilization or underutilization problem often occurring in bike sharing system. At the same time, station transfer demand prediction is helpful to bike station layout and optimization of the number of public bikes within the station. Traditional traffic demand prediction methods, such as gravity model, cannot be easily adapted to the problem of forecasting bike station transfer demand due to the difficulty in defining impedance and distinct characteristics of bike stations (Xu et al. 2013). Therefore, this paper proposes a prediction method based on Markov chain model. The proposed model is evaluated based on field data collected from Zhongshan City bike sharing system. The daily production and attraction of stations are forecasted. The experimental results show that the model of this paper performs higher forecasting accuracy and better generalization ability.

scholarly journals Network and station-level bike-sharing system prediction: a San Francisco bay area case study

2021 ◽  
pp. 1-11
Author(s):  
Huthaifa I. Ashqar ◽  
Mohammed Elhenawy ◽  
Hesham A. Rakha ◽  
Mohammed Almannaa ◽  
Leanna House
Keyword(s):  
San Francisco ◽  
San Francisco Bay ◽  
San Francisco Bay Area ◽  
Bay Area ◽  
Bike Sharing

A Qualitative Study of Ecstasy Sellers in the San Francisco Bay Area

2004 ◽  
Author(s):  
Sheigla Murphy ◽  
Paloma Sales ◽  
Micheline Duterte ◽  
Camille Jacinto
Keyword(s):  
Qualitative Study ◽  
San Francisco ◽  
San Francisco Bay ◽  
San Francisco Bay Area ◽  
Bay Area

The “Japanese Turn” in Fine Dining in the United States, 1980–2020

2020 ◽  
Vol 20 (2) ◽  
pp. 45-54
Author(s):  
Samuel H. Yamashita
Keyword(s):  
United States ◽  
New York ◽  
Los Angeles ◽  
San Francisco ◽  
San Francisco Bay Area ◽  
The United States ◽  
First Century ◽  
Further Training ◽  
Bay Area ◽  
Wide Acceptance

In the 1970s, Japanese cooks began to appear in the kitchens of nouvelle cuisine chefs in France for further training, with scores more arriving in the next decades. Paul Bocuse, Alain Chapel, Joël Robuchon, and other leading French chefs started visiting Japan to teach, cook, and sample Japanese cuisine, and ten of them eventually opened restaurants there. In the 1980s and 1990s, these chefs' frequent visits to Japan and the steady flow of Japanese stagiaires to French restaurants in Europe and the United States encouraged a series of changes that I am calling the “Japanese turn,” which found chefs at fine-dining establishments in Los Angeles, New York City, and later the San Francisco Bay Area using an ever-widening array of Japanese ingredients, employing Japanese culinary techniques, and adding Japanese dishes to their menus. By the second decade of the twenty-first century, the wide acceptance of not only Japanese ingredients and techniques but also concepts like umami (savory tastiness) and shun (seasonality) suggest that Japanese cuisine is now well known to many American chefs.

Cyborg Jotería Pedagogies: Latinx Drag Queens Leveraging Communication Ecologies in the Age of the Digital and Social Displacement

2020 ◽  
Vol 14 (2) ◽  
pp. 44-66
Author(s):  
José Ramón Lizárraga ◽  
Arturo Cortez
Keyword(s):  
San Francisco ◽  
San Francisco Bay ◽  
San Francisco Bay Area ◽  
Digital Technologies ◽  
Physical World ◽  
Political Issues ◽  
Drag Queen ◽  
Bay Area ◽  
Online Presence ◽  
Drag Queens

Researchers and practitioners have much to learn from drag queens, specifically Latinx queens, as they leverage everyday queerness and brownness in ways that contribute to pedagogy locally and globally, individually and collectively. Drawing on previous work examining the digital queer gestures of drag queen educators (Lizárraga & Cortez, 2019), this essay explores how non-dominant people that exist and fluctuate in the in-between of boundaries of gender, race, sexuality, the physical, and the virtual provide pedagogical overtures for imagining and organizing for new possible futures that are equitable and just. Further animated by Donna Haraway’s (2006) influential feminist post-humanist work, we interrogate how Latinx drag queens as cyborgs use digital technologies to enhance their craft and engage in powerful pedagogical moves. This essay draws from robust analyses of the digital presence of and interviews with two Latinx drag queens in the San Francisco Bay Area, as well as the online presence of a Xicanx doggie drag queen named RuPawl. Our participants actively drew on their liminality to provoke and mobilize communities around socio-political issues. In this regard, we see them engaging in transformative public cyborg jotería pedagogies that are made visible and historicized in the digital and physical world.

An Efficient Markov Chain Model for the Simulation of Heterogeneous Soil Structure

2004 ◽  
Vol 68 (2) ◽  
pp. 346 ◽  
Author(s):  
Keijan Wu ◽  
Naoise Nunan ◽  
John W. Crawford ◽  
Iain M. Young ◽  
Karl Ritz
Keyword(s):  
Markov Chain ◽  
Soil Structure ◽  
Markov Chain Model ◽  
Chain Model ◽  
Heterogeneous Soil
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