Neural Network–Based Intelligent Compaction Analyzer for Estimating Compaction Quality of Hot Asphalt Mixes-Reference-Cited by-同舟云学术

Neural Network–Based Intelligent Compaction Analyzer for Estimating Compaction Quality of Hot Asphalt Mixes

Published:2011-09 Issue:9 Volume:137 Page:634-644
ISSN:0733-9364
Container-title:Journal of Construction Engineering and Management
language:en
Short-container-title:J. Constr. Eng. Manage.

Author:

Commuri Sesh¹²³,Mai Anh T.¹²³,Zaman Musharraf¹²³

Affiliation:

1. Associate Professor, School of Electrical and Computer Engineering, Univ. of Oklahoma, 110 West Boyd St., Devon Energy Hall 432, Norman, OK 73019 (corresponding author).

2. Ph.D. Candidate, School of Electrical and Computer Engineering, Univ. of Oklahoma, 110 West Boyd St., Devon Energy Hall 150, Norman, OK 73019.

3. Professor, Associate Dean for Research, College of Engineering, Univ. of Oklahoma, 202 W. Boyd St., Room 107, Norman, OK 73019-1023.

Publisher

American Society of Civil Engineers (ASCE)

Subject

Strategy and Management,Industrial relations,Building and Construction,Civil and Structural Engineering

Link

http://ascelibrary.org/doi/pdf/10.1061/%28ASCE%29CO.1943-7862.0000343

Reference26 articles.

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2. AASHTO. (2004). “Standard method of test for the moisture-density relations of soils using a 2.5-kg (5.5-lb) rammer and a 305-mm (12-in.) drop.” T 99 Washington DC.

3. Ammann Schweiz AG. (2007). “Intelligent compaction.” 〈http://www.ammann-group.com/en/home/technology/intelligent-ground-compaction/〉 (Oct. 1 2007).

4. Ayres M. Jr. and Witczak M. W. (1998). “AYMA: Mechanistic probabilistic system to evaluate flexible pavement performance.” Transportation Research Record 1629 Transportation Research Board Washington DC. 137–148.

5. BOMAG. (2007). “VarioControl.” 〈http://www.bomag.com/world/EN/variocontrol.htm〉 (Oct. 1 2007).

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