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Feature selection is an important part during the process of qualitative and quantitative analysis of infrared spectrum. In order to solve the disadvantage of traditional methods, such as multi-parameters, slow convergence, poor accuracy, prone to premature, etc. a novel feature selection firefly algorithm was proposed, which combined the basic firely algorithm and Lévy flights search strategy. The algorithm was experimented and the experimental results show that the novel algorithm is better suited to handle feature selection of infrared spectrum. The feasibility and effectiveness of the method are demonstrated.

A Novel firefly algorithm of solving feature selection of infrared spectrum