The Potential Application of a New Intelligent Based Approach in Predicting the Tensile Strength of Rock
Tensile strength (TS) of rock is one of the important properties in design process of construction civil works such as foundations and tunnels. Brazilian tensile strength (BTS) or splitting test is considered as a well-known method in evaluating TS. The present study attempts to propose a novel meta...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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IEEE
2020-01-01
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| Series: | IEEE Access |
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| Online Access: | https://ieeexplore.ieee.org/document/9035399/ |
| _version_ | 1818579534340947968 |
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| author | Mahdi Hasanipanah Wengang Zhang Danial Jahed Armaghani Hima Nikafshan Rad |
| author_facet | Mahdi Hasanipanah Wengang Zhang Danial Jahed Armaghani Hima Nikafshan Rad |
| author_sort | Mahdi Hasanipanah |
| collection | DOAJ |
| description | Tensile strength (TS) of rock is one of the important properties in design process of construction civil works such as foundations and tunnels. Brazilian tensile strength (BTS) or splitting test is considered as a well-known method in evaluating TS. The present study attempts to propose a novel metaheuristic approach for the indirect measurement of BTS. This new approach is based on the firefly algorithm (FA) for training and optimizing the consequent parameters of the adaptive neuro-fuzzy inference system (ANFIS). The rock samples collected from a tunnel in Malaysia were tested in the laboratory for the purpose of providing a database consisting of totally 80 samples for analysis. Then, the statistical metrics such as coefficient of determination (R<sup>2</sup>) were used to examine the acceptability of the proposed ANFIS-FA and ANFIS models. Finally, it was concluded that the ANFIS-FA (with the R<sup>2</sup> of 0.982) can be effectively used as a robust model to predict BTS. |
| first_indexed | 2024-12-16T07:03:14Z |
| format | Article |
| id | doaj.art-e465a8c975a1463c8a62da3c9a078f23 |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-12-16T07:03:14Z |
| publishDate | 2020-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-e465a8c975a1463c8a62da3c9a078f232022-12-21T22:40:06ZengIEEEIEEE Access2169-35362020-01-018571485715710.1109/ACCESS.2020.29806239035399The Potential Application of a New Intelligent Based Approach in Predicting the Tensile Strength of RockMahdi Hasanipanah0Wengang Zhang1Danial Jahed Armaghani2https://orcid.org/0000-0001-8171-6403Hima Nikafshan Rad3https://orcid.org/0000-0002-5917-7818Institute of Research and Development, Duy Tan University, Da Nang, VietnamSchool of Civil Engineering, Chongqing University, Chongqing, ChinaModeling Evolutionary Algorithms Simulation and Artificial Intelligence, Faculty of Electrical & Electronics Engineering, Ton Duc Thang University, Ho Chi Minh City, VietnamCollege of Computer Science, Tabari University, Babol, IranTensile strength (TS) of rock is one of the important properties in design process of construction civil works such as foundations and tunnels. Brazilian tensile strength (BTS) or splitting test is considered as a well-known method in evaluating TS. The present study attempts to propose a novel metaheuristic approach for the indirect measurement of BTS. This new approach is based on the firefly algorithm (FA) for training and optimizing the consequent parameters of the adaptive neuro-fuzzy inference system (ANFIS). The rock samples collected from a tunnel in Malaysia were tested in the laboratory for the purpose of providing a database consisting of totally 80 samples for analysis. Then, the statistical metrics such as coefficient of determination (R<sup>2</sup>) were used to examine the acceptability of the proposed ANFIS-FA and ANFIS models. Finally, it was concluded that the ANFIS-FA (with the R<sup>2</sup> of 0.982) can be effectively used as a robust model to predict BTS.https://ieeexplore.ieee.org/document/9035399/Tensile strengthbrazilian tensile strengthANFISfirefly algorithm |
| spellingShingle | Mahdi Hasanipanah Wengang Zhang Danial Jahed Armaghani Hima Nikafshan Rad The Potential Application of a New Intelligent Based Approach in Predicting the Tensile Strength of Rock IEEE Access Tensile strength brazilian tensile strength ANFIS firefly algorithm |
| title | The Potential Application of a New Intelligent Based Approach in Predicting the Tensile Strength of Rock |
| title_full | The Potential Application of a New Intelligent Based Approach in Predicting the Tensile Strength of Rock |
| title_fullStr | The Potential Application of a New Intelligent Based Approach in Predicting the Tensile Strength of Rock |
| title_full_unstemmed | The Potential Application of a New Intelligent Based Approach in Predicting the Tensile Strength of Rock |
| title_short | The Potential Application of a New Intelligent Based Approach in Predicting the Tensile Strength of Rock |
| title_sort | potential application of a new intelligent based approach in predicting the tensile strength of rock |
| topic | Tensile strength brazilian tensile strength ANFIS firefly algorithm |
| url | https://ieeexplore.ieee.org/document/9035399/ |
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