MARC details
| 000 -LEADER |
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| fixed length control field |
03014nam a2200253 a 4500 |
| 001 - CONTROL NUMBER |
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| control field |
vtls000075371 |
| 003 - CONTROL NUMBER IDENTIFIER |
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| control field |
KUKTEM |
| 005 - DATE AND TIME OF LATEST TRANSACTION |
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| control field |
20251114204553.0 |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION |
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| fixed length control field |
131011t2013 my da f m 000 0 eng d |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER |
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| International Standard Book Number |
THE0002501(Local) |
| 039 #9 - LEVEL OF BIBLIOGRAPHIC CONTROL AND CODING DETAIL [OBSOLETE] |
|---|
| Level of rules in bibliographic description |
201905271552 |
| Level of effort used to assign nonsubject heading access points |
shamsul |
| Level of effort used to assign subject headings |
201710061523 |
| Level of effort used to assign classification |
aishah |
| Level of effort used to assign subject headings |
201311201628 |
| Level of effort used to assign classification |
nabilah |
| -- |
201310111624 |
| -- |
nabilah |
| 040 ## - CATALOGING SOURCE |
|---|
| Original cataloging agency |
UMP |
| 090 ## - LOCALLY ASSIGNED LC-TYPE CALL NUMBER (OCLC); LOCAL CALL NUMBER (RLIN) |
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| Classification number (OCLC) (R) ; Classification number, CALL (RLIN) (NR) |
TA439 .H33 2013 rs Thesis |
| 100 1# - MAIN ENTRY--PERSONAL NAME |
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| Personal name |
Hadiwidodo, Yoyok Setyo |
| 245 10 - TITLE STATEMENT |
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| Title |
Smooth support vector regression (SSVR) modelling of self-compacting concrete properties / |
| Statement of responsibility, etc. |
Yoyok Setyo Hadiwidodo |
| 260 ## - PUBLICATION, DISTRIBUTION, ETC. |
|---|
| Place of publication, distribution, etc. |
Kuantan, Pahang : |
| Name of publisher, distributor, etc. |
UMP, |
| Date of publication, distribution, etc. |
2013 |
| 300 ## - PHYSICAL DESCRIPTION |
|---|
| Extent |
xviii, 155 p. : |
| Other physical details |
ill. ; |
| Dimensions |
30 cm. + |
| Accompanying material |
1 CD-ROM |
| 502 ## - DISSERTATION NOTE |
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| Dissertation note |
Thesis (PhD in Civil Engineering) -- Universiti Malaysia Pahang – 2013 |
| 504 ## - BIBLIOGRAPHY, ETC. NOTE |
|---|
| Bibliography, etc. note |
Bibliography : p. 133-142 |
| 520 3# - SUMMARY, ETC. |
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| Summary, etc. |
Self-compacting concrete (SCC) is a type of concrete that can flow under its own weight without vibration, filling small interstices of formwork, passing through complicated geometrical configurations, be pumped through long distances and resist segregation. SCC is a complex material, which makes modelling its behaviour a very difficult task. SCC constituent materials and mix proportions which must be properly selected to achieve these flow properties required. The effects of any changes in materials or mix proportions on fresh and hardened concrete performance must be considered in evaluating SCC. It is crucial to use a systematic approach for identifying optimal mixes and investigates the most effective factors on SCC properties under a set of constraints. Due to this reason Taguchi method with the L18 (36) orthogonal array is used in this study to investigate the properties of SCC. Taguchi method is a promising approach for optimizing mix proportions of SCC to meet several fresh concrete properties. Taguchi method can simplify the test procedure required to optimize mix proportion of SCC by reducing the number of trial mixes. This study has shown that it is possible to model SCC which fulfilling its criteria. The application of the Taguchi method gave the optimal mix design proportions for fresh properties and hardened properties as well. This study has also demonstrated the capability of regression analysis and Smooth Support Vector Regression (SSVR) modelling to predict the properties of SCC. The performance of the proposed method is evaluated using a coefficient of determination (R2) and mean square error (MSE). Results have shown this model is accurate in prediction of the properties of SCC because it has maximum R2 and minimum MSE. The performance of the proposed method is also verified by comparing the predicted levels with actual values. It can be concluded that SSVR method can predict properties of self-compacting concrete with higher estimation accuracy. |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name entry element |
Concrete |
| General subdivision |
Mixing |
| 856 40 - ELECTRONIC LOCATION AND ACCESS |
|---|
| Uniform Resource Identifier |
<a href="http://ecollib.ump.edu.my/24271/">http://ecollib.ump.edu.my/24271/</a> |
| Public note |
Library access only |