Explaining Heterogeneity in Pavement Deterioration: Clusterwise Linear Regression Model-Reference-Cited by-同舟云学术

Explaining Heterogeneity in Pavement Deterioration: Clusterwise Linear Regression Model

Published:2014-06 Issue:2 Volume:20 Page:04014005
ISSN:1076-0342
Container-title:Journal of Infrastructure Systems
language:en
Short-container-title:J. Infrastruct. Syst.

Author:

Zhang Weizeng¹,Durango-Cohen Pablo L.²

Affiliation:

1. Ph.D. Candidate, Dept. of Civil and Environmental Engineering, Northwestern Univ., 2145 Sheridan Rd., A310, Evanston, IL 60208-3109.

2. Associate Professor, Dept. of Civil and Environmental Engineering, Northwestern Univ., 2145 Sheridan Rd., A332, Evanston, IL 60208-3109 (corresponding author).

Publisher

American Society of Civil Engineers (ASCE)

Subject

Civil and Structural Engineering

Link

http://ascelibrary.org/doi/pdf/10.1061/%28ASCE%29IS.1943-555X.0000182

Reference39 articles.

1. Repeated Measurement Data Analysis in Pavement Deterioration Modeling

2. Development of a Pavement Rutting Model from Experimental Data

3. Using Classification Trees for Predicting National Bridge Inventory Condition Ratings

4. Cautionary Remarks on the Use of Clusterwise Regression

5. Multicriterion Clusterwise Regression for Joint Segmentation Settings: An Application to Customer Value

Cited by 20 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. An appraisal of statistical and probabilistic models in highway pavements;Turkish Journal of Engineering;2024-04-30

2. Climate-induced deterioration prediction for bridges: an evolutionary computing-based framework;Innovative Infrastructure Solutions;2024-03-24

3. Regression;Data Analysis in Pavement Engineering;2024

4. Multi-Objective Optimization of Maintenance, Rehabilitation, and Reconstruction Decision Making Considering Safety;Transportation Research Record: Journal of the Transportation Research Board;2023-05-29

5. Methods and Applications of Clusterwise Linear Regression: A Survey and Comparison;ACM Transactions on Knowledge Discovery from Data;2023-02-22