Transportation policy profiles of Chinese city clusters: A mixed methods approach

Transportation policy profiles of Chinese city clusters: A mixed methods approach

Chinese cities have experienced diverse urbanization and motorization trends that present distinct challenges for municipal transportation policymaking. However, there is no systematic understanding of the unique motorization and urbanization trends of Chinese cities and how physical characteristics...

Full description

Bibliographic Details
Main Authors:	Joanna Moody, Shenhao Wang, Jungwoo Chun, Xuenan Ni, Jinhua Zhao
Format:	Article
Language:	English
Published:	Elsevier 2019-09-01
Series:	Transportation Research Interdisciplinary Perspectives
Subjects:	Transportation policy Mixed methods Time series clustering Chinese cities
Online Access:	http://www.sciencedirect.com/science/article/pii/S2590198219300533

Similar Items

Transportation policy profiles of Chinese city clusters: A mixed methods approach
by: Moody, Joanna Charlotte, et al.
Published: (2020)

Mapping the Provincial Food Security Conditions in Indonesia Using Cluster Ensemble-Based Mixed Data Clustering-Robust Clustering with Links (CEBMDC-ROCK)
by: Dani, A.T.R, et al.
Published: (2023)

A generic Chinese PAT tree data structure for Chinese documents clustering.
Published: (2002)

Effect of Mixing Regimes on Cow Manure Digestion in Impeller Mixed, Unmixed and Chinese Dome Digesters
by: Abiodun O. Jegede, et al.
Published: (2019-07-01)

What prompts the adoption of car restriction policies among Chinese cities
by: Wang, Shenhao, et al.
Published: (2020)

Energy transition pathways amongst low-income urban households: A mixed method clustering approach
by: André P. Neto-Bradley, et al.
Published: (2021-01-01)

Time Series Clustering with Topological and Geometric Mixed Distance
by: Yunsheng Zhang, et al.
Published: (2021-05-01)

An Exploration of Chineseness in Mindanao, Philippines: The Case of Zamboanga City
by: Melodina S. Cruz
Published: (2017-12-01)

Survey of State-of-the-Art Mixed Data Clustering Algorithms
by: Amir Ahmad, et al.
Published: (2019-01-01)

Russian-Chinese families in the 20th century: Emergence and characteristics1
by: Vladimir G. Datsyshen, et al.
Published: (2019-12-01)

Cultures unfolding: experiences of Chinese-Hungarian mixed couples in Hungary
by: Nóra Kovács
Published: (2015-10-01)

Using Permutations for Hierarchical Clustering of Time Series
by: Jose S. Cánovas, et al.
Published: (2019-03-01)

Intensification of Development of Mixed Transportation of Freight in Ukraine through Formation of the Network of Transportation and Logistic Centres and Transportation and Logistic Clusters
by: Karpenko Oksana O., et al.
Published: (2013-11-01)

Clustering Mixed Numeric and Categorical Data With Cuckoo Search
by: Jinchao Ji, et al.
Published: (2020-01-01)

Clustering Mixed Data Based on Density Peaks and Stacked Denoising Autoencoders
by: Baobin Duan, et al.
Published: (2019-02-01)

Big Data Analytics for Discovering Electricity Consumption Patterns in Smart Cities
by: Rubén Pérez-Chacón, et al.
Published: (2018-03-01)

Functional Mixed Data Clustering with Fourier Basis Smoothing
by: Amartey, Ishmael
Published: (2021)

Critical indicators of sustainability for mixed-use buildings in Lagos, Nigeria
by: Shakirat Folashade Salami, et al.
Published: (2021-02-01)

kamila: Clustering Mixed-Type Data in R and Hadoop
by: Alexander H. Foss, et al.
Published: (2018-02-01)

Exploring point zero: a study of 20 Chinese cities
by: Qi Zhou, et al.
Published: (2020-07-01)

ENTREPRENEURIAL ACTIVITY IN ROMANIA – A TIME SERIES CLUSTERING ANALYSIS AT THE NUTS3 LEVEL
by: Sipos-Gug Sebastian, et al.
Published: (2013-07-01)

Clustering Data of Mixed Categorical and Numerical Type With Unsupervised Feature Learning
by: Dao Lam, et al.
Published: (2015-01-01)

Whole Time Series Data Streams Clustering: Dynamic Profiling of the Electricity Consumption
by: Krzysztof Gajowniczek, et al.
Published: (2020-12-01)

Filtering and clustering GPS time series for lifespace analysis
by: Morrison, Laura May
Published: (2013)

Breastfeeding practices 2008–2009 among Chinese mothers living in Ireland: a mixed methods study
by: Qianling Zhou, et al.
Published: (2020-01-01)

Data Mining in the Mixed Methods: Application to the Study of the Psychological Profiles of Athletes
by: José L. Pastrana, et al.
Published: (2019-12-01)

Mixed Network Clustering with Multiple Ground Stations and Nodes Preferences
by: Traore, Oumar, et al.
Published: (2010)

A Methodology for Energy Load Profile Forecasting Based on Intelligent Clustering and Smoothing Techniques
by: Jamer Jiménez Mares, et al.
Published: (2020-08-01)

Differentially Private Mixed Data Release Algorithm Based on k-prototype Clustering
by: QU Jingjing, CAI Ying, FAN Yanfang, XIA Hongke
Published: (2021-01-01)

Air Pollution as a Cause of Obesity: Micro-Level Evidence from Chinese Cities
by: Zhiming Yang, et al.
Published: (2019-11-01)

Chinese Fans’ Patriotism Creating Quandary in the Digital Media Era
by: Shiyu Zheng
Published: (2020-12-01)

Cluster_Based Profile Monitoring in Phase I Analysis
by: Chen, Yajuan
Published: (2014)

Stereotypical Chinese Accent of English in American TV Series
by: Qu, Dake
Published: (2010)

A Multi-View Clustering Algorithm for Mixed Numeric and Categorical Data
by: Jinchao Ji, et al.
Published: (2021-01-01)

A benchmark study on time series clustering
by: Ali Javed, et al.
Published: (2020-09-01)

Time series clustering in large data sets
by: Jiří Fejfar, et al.
Published: (2011-01-01)

Visualizing Profiles of Large Datasets of Weighted and Mixed Data
by: Aurea Grané, et al.
Published: (2021-04-01)

Inference for Clustered Mixed Outcomes from a Multivariate Generalized Linear Mixed Model
by: Chen, Hsiang-Chun
Published: (2013)

Ligand Substitution Studies in the Tetracobalt Cluster Co₄(CO)₁₀([mu]₄-PPh₂) and Synthesis and Reactivity Studies in the Fe₂Pt and FeCo₂ Mixed-metal Clusters
by: Don, Ming-jaw
Published: (1991)

Profile of the Paraoxonase 1 (PON1) Gene 192Q/R Polymorphism and Clinical Associations among Older Singaporean Chinese with Alzheimer's and Mixed Dementia
by: Dennis C.C. Seow, et al.
Published: (2016-02-01)