Analysis of Factors Affecting the Success of Sustainable Development Projects with the Help of Machine Learning Tools
Sustainable development projects are a group of development projects created with the aim of sustainable urban growth and development. To achieve development, it is essential to pay attention to the existence of projects. The point to consider is the threat of these expensive assets by all kinds of...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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Wiley
2022-01-01
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| Series: | Discrete Dynamics in Nature and Society |
| Online Access: | http://dx.doi.org/10.1155/2022/1956879 |
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| _version_ | 1849308992107446272 |
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| author | Zhi-Jun Chen Tsung-Shun Hsieh Seyed Mehdi Mousavi Davoudi |
| author_facet | Zhi-Jun Chen Tsung-Shun Hsieh Seyed Mehdi Mousavi Davoudi |
| author_sort | Zhi-Jun Chen |
| collection | DOAJ |
| description | Sustainable development projects are a group of development projects created with the aim of sustainable urban growth and development. To achieve development, it is essential to pay attention to the existence of projects. The point to consider is the threat of these expensive assets by all kinds of risks, such as floods, earthquakes, wars, mistakes, and price fluctuations, during the life cycle of projects from the beginning of their idea to the end of their useful life. Hence, the main objective of the study is to analyze the criteria and factors of project success and different machine learning strategies to achieve success and predict specific construction performance. To meet that aim, the research employs the descriptive approach, and analytical and logical aspects are derived from various sources such as research articles, published materials, online websites, books, and articles. The study’s results reveal that employing machine learning tools and algorithms to create a link between project success factors and criteria and prediction can bring multiple advantages, including high accuracy, ease of use, and inference for decision-making. It can be concluded that algorithmic solutions could be integrated in a manner that project managers can adequately utilize to enhance project success by eliminating potential risks and guiding the project toward attaining its objectives. |
| format | Article |
| id | doaj-art-0c3e113e1bf0489c938f5c9dbac95d77 |
| institution | Kabale University |
| issn | 1607-887X |
| language | English |
| publishDate | 2022-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Discrete Dynamics in Nature and Society |
| spelling | doaj-art-0c3e113e1bf0489c938f5c9dbac95d772025-08-20T03:54:19ZengWileyDiscrete Dynamics in Nature and Society1607-887X2022-01-01202210.1155/2022/1956879Analysis of Factors Affecting the Success of Sustainable Development Projects with the Help of Machine Learning ToolsZhi-Jun Chen0Tsung-Shun Hsieh1Seyed Mehdi Mousavi Davoudi2Senior Artist and CraftsmanKrirk UniversityDepartment of ManagementSustainable development projects are a group of development projects created with the aim of sustainable urban growth and development. To achieve development, it is essential to pay attention to the existence of projects. The point to consider is the threat of these expensive assets by all kinds of risks, such as floods, earthquakes, wars, mistakes, and price fluctuations, during the life cycle of projects from the beginning of their idea to the end of their useful life. Hence, the main objective of the study is to analyze the criteria and factors of project success and different machine learning strategies to achieve success and predict specific construction performance. To meet that aim, the research employs the descriptive approach, and analytical and logical aspects are derived from various sources such as research articles, published materials, online websites, books, and articles. The study’s results reveal that employing machine learning tools and algorithms to create a link between project success factors and criteria and prediction can bring multiple advantages, including high accuracy, ease of use, and inference for decision-making. It can be concluded that algorithmic solutions could be integrated in a manner that project managers can adequately utilize to enhance project success by eliminating potential risks and guiding the project toward attaining its objectives.http://dx.doi.org/10.1155/2022/1956879 |
| spellingShingle | Zhi-Jun Chen Tsung-Shun Hsieh Seyed Mehdi Mousavi Davoudi Analysis of Factors Affecting the Success of Sustainable Development Projects with the Help of Machine Learning Tools Discrete Dynamics in Nature and Society |
| title | Analysis of Factors Affecting the Success of Sustainable Development Projects with the Help of Machine Learning Tools |
| title_full | Analysis of Factors Affecting the Success of Sustainable Development Projects with the Help of Machine Learning Tools |
| title_fullStr | Analysis of Factors Affecting the Success of Sustainable Development Projects with the Help of Machine Learning Tools |
| title_full_unstemmed | Analysis of Factors Affecting the Success of Sustainable Development Projects with the Help of Machine Learning Tools |
| title_short | Analysis of Factors Affecting the Success of Sustainable Development Projects with the Help of Machine Learning Tools |
| title_sort | analysis of factors affecting the success of sustainable development projects with the help of machine learning tools |
| url | http://dx.doi.org/10.1155/2022/1956879 |
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