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Based on an analysis of traditional optimization algorithms, this paper proposes a novel sensor optimization criterion that combines the effective independence (EFI) method with the modal strain energy (MSE) method. Considering the complex structure and enormous degrees of freedom (DOFs) of modern concrete arch dam, a quantum genetic algorithm (QGA) is used to optimize the corresponding sensor network on the upstream surface of a dam. Finally, this study uses a specific concrete arch dam as an example and determines the optimal sensor placement using the proposed method. By comparing the results with the traditional optimization methods, the proposed method is shown to maximize the spatial intersection angle among the modal vectors of sensor network and can effectively resist ambient perturbations, which will make the identified modal parameters more precise.<\/jats:p>","DOI":"10.1155\/2016\/2567305","type":"journal-article","created":{"date-parts":[[2016,2,1]],"date-time":"2016-02-01T21:03:01Z","timestamp":1454360581000},"page":"1-10","source":"Crossref","is-referenced-by-count":15,"title":["Determining the Optimal Placement of Sensors on a Concrete Arch Dam Using a Quantum Genetic Algorithm"],"prefix":"10.1155","volume":"2016","author":[{"given":"Kai","family":"Zhu","sequence":"first","affiliation":[{"name":"State Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering, Hohai University, Nanjing 210098, China"},{"name":"National Engineering Research Center of Water Resources Efficient Utilization and Engineering Safety, Hohai 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