Predicting the climbing rate of slip formwork systems using linear biogeography-based programming

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@Article{GOLAFSHANI:2018:ASCa,

• author = "Emadaldin Mohammadi Golafshani and Siamak Talatahari",
• title = "Predicting the climbing rate of slip formwork systems using linear biogeography-based programming",
• journal = "Applied Soft Computing",
• year = "2018",
• volume = "70",
• pages = "263--278",
• month = sep,
• keywords = "genetic algorithms, genetic programming, Slip formwork, Climbing rate, Linear biogeography-based programming, Linear genetic programming",
• ISSN = "1568-4946",
• DOI = "doi:10.1016/j.asoc.2018.05.036",
• URL = "http://www.sciencedirect.com/science/article/pii/S1568494618303119",
• abstract = "Nowadays, it is undeniable necessity to select a fast and appropriate method for construction of high rise concrete structures. Slip formwork technology, as an automatic formwork system, has many advantages for high rise buildings and can reduce the construction time and costs. However, the climbing rate of slip formwork systems is a challenging task and depends on different factors. In this paper, the potential factors in calculating the climbing rate were identified. Then, a comprehensive database including 81 slip formwork projects in Iran was gathered. Afterwards, a symbolic regression method called linear biogeography-based programming was introduced and applied for extracting a formula that obtains a good climbing rate of slip formwork systems. For evaluating the performance of the proposed method, artificial neural network and linear genetic programming were used as well. The results show that the proposed formulation has good agreement with actual values of climbing rate of slip forming systems with low error and complexity and find it to be quite confident. Moreover, weather conditions criteria is known as the most effective parameter in climbing the rate of slip formwork systems based on the performed sensitivity analysis",
• notes = "Department of Civil Engineering, Architecture and Art, Science and Research Branch, Islamic Azad University, Tehran, Iran",

}

Genetic Programming entries for Emadaldin Mohammadi Golafshani Siamak Talatahari

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