PRESENTING KOHONEN NEURAL NETWORK MODEL FOR DETERMINING THE CONTRIBUTION OF EACH FACTOR INVOLVED IN THE DELAYS (CASE STUDY: ....)
With proper investigation of project delays, they can be made as lesson learning. So, in this research, a method has been presented to offer network- based pattern for identifying th...
| Main Authors: | , , |
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| Format: | Article |
| Language: | fas |
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Sharif University of Technology
2018-11-01
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| Series: | مهندسی عمران شریف |
| Subjects: | |
| Online Access: | https://sjce.journals.sharif.edu/article_1423_d317fd3ad27bad8d589e769b85f70333.pdf |
| _version_ | 1797736751021686784 |
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| author | E. Eshtehardian p. Shahsavand M. Moazzezi Farhadi Far |
| author_facet | E. Eshtehardian p. Shahsavand M. Moazzezi Farhadi Far |
| author_sort | E. Eshtehardian |
| collection | DOAJ |
| description | With proper investigation of project delays, they can be made as lesson learning. So, in this research, a method has been presented to offer network- based pattern for identifying the reasons of delays. For this purpose, reasons of delay in Tehran-Shomal highway are indicated in a table for each group involved in the mentioned project and the main source of delays of the four factors involved in the project: employer, contractor (delay of materials and equipment and human resource, supplier delays, delay in transportation and warehouse that is the prerogative of contractor), consultant, and external factors were identified and categorized. Then, according to the experts' opinions and interviews conducted with agents working in projects, all items of
delays have been scored from 0 to 10 since 1994 to 2015 in two cases:, the possibility of delays in the project of Tehran-Shomal and the intensity rate and the impact of delays. In the last section, for the first time, delays in Kohonen self-organizing neural network have been evaluated using MATLAB in the program of SOFM. Delays in research findings that are not distinguished in two ways are not distinct, and overlapp each other. |
| first_indexed | 2024-03-12T13:18:30Z |
| format | Article |
| id | doaj.art-74d2d29258ab42a8845a404619f45dac |
| institution | Directory Open Access Journal |
| issn | 2676-4768 2676-4776 |
| language | fas |
| last_indexed | 2024-03-12T13:18:30Z |
| publishDate | 2018-11-01 |
| publisher | Sharif University of Technology |
| record_format | Article |
| series | مهندسی عمران شریف |
| spelling | doaj.art-74d2d29258ab42a8845a404619f45dac2023-08-26T10:17:34ZfasSharif University of Technologyمهندسی عمران شریف2676-47682676-47762018-11-0134.23.210511610.24200/j30.2018.14231423PRESENTING KOHONEN NEURAL NETWORK MODEL FOR DETERMINING THE CONTRIBUTION OF EACH FACTOR INVOLVED IN THE DELAYS (CASE STUDY: ....)E. Eshtehardian0p. Shahsavand1M. Moazzezi Farhadi Far2Faculty of Architecture University of Tarbiat ModaresFaculty of Architecture University of TehranFaculty of Electrical Engineering University of Science and TechnologyWith proper investigation of project delays, they can be made as lesson learning. So, in this research, a method has been presented to offer network- based pattern for identifying the reasons of delays. For this purpose, reasons of delay in Tehran-Shomal highway are indicated in a table for each group involved in the mentioned project and the main source of delays of the four factors involved in the project: employer, contractor (delay of materials and equipment and human resource, supplier delays, delay in transportation and warehouse that is the prerogative of contractor), consultant, and external factors were identified and categorized. Then, according to the experts' opinions and interviews conducted with agents working in projects, all items of delays have been scored from 0 to 10 since 1994 to 2015 in two cases:, the possibility of delays in the project of Tehran-Shomal and the intensity rate and the impact of delays. In the last section, for the first time, delays in Kohonen self-organizing neural network have been evaluated using MATLAB in the program of SOFM. Delays in research findings that are not distinguished in two ways are not distinct, and overlapp each other.https://sjce.journals.sharif.edu/article_1423_d317fd3ad27bad8d589e769b85f70333.pdftehran-shomal highway delayskohonen self-organizing neural networklesson learning |
| spellingShingle | E. Eshtehardian p. Shahsavand M. Moazzezi Farhadi Far PRESENTING KOHONEN NEURAL NETWORK MODEL FOR DETERMINING THE CONTRIBUTION OF EACH FACTOR INVOLVED IN THE DELAYS (CASE STUDY: ....) مهندسی عمران شریف tehran-shomal highway delays kohonen self-organizing neural network lesson learning |
| title | PRESENTING KOHONEN NEURAL NETWORK MODEL FOR DETERMINING THE CONTRIBUTION OF EACH FACTOR INVOLVED IN THE DELAYS (CASE STUDY: ....) |
| title_full | PRESENTING KOHONEN NEURAL NETWORK MODEL FOR DETERMINING THE CONTRIBUTION OF EACH FACTOR INVOLVED IN THE DELAYS (CASE STUDY: ....) |
| title_fullStr | PRESENTING KOHONEN NEURAL NETWORK MODEL FOR DETERMINING THE CONTRIBUTION OF EACH FACTOR INVOLVED IN THE DELAYS (CASE STUDY: ....) |
| title_full_unstemmed | PRESENTING KOHONEN NEURAL NETWORK MODEL FOR DETERMINING THE CONTRIBUTION OF EACH FACTOR INVOLVED IN THE DELAYS (CASE STUDY: ....) |
| title_short | PRESENTING KOHONEN NEURAL NETWORK MODEL FOR DETERMINING THE CONTRIBUTION OF EACH FACTOR INVOLVED IN THE DELAYS (CASE STUDY: ....) |
| title_sort | presenting kohonen neural network model for determining the contribution of each factor involved in the delays case study |
| topic | tehran-shomal highway delays kohonen self-organizing neural network lesson learning |
| url | https://sjce.journals.sharif.edu/article_1423_d317fd3ad27bad8d589e769b85f70333.pdf |
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