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• W2045647632 abstract "Screening of relevant factors using Plackett-Burman designs is usual in analytical chemistry. It relies on the assumption that factor interactions are negligible; however, failure of recognizing such interactions may lead to incorrect results. Factor associations can be revealed by feature selection techniques such as ant colony optimization. This method has been combined with a Monte Carlo approach, developing a new algorithm for assessing both main and interaction terms when analyzing the influence of experimental factors through a Plackett-Burman design of experiments. The results for both simulated and analytically relevant experimental systems show excellent agreement with previous approaches, highlighting the importance of considering potential interactions when conducting a screening search." @default.
• W2045647632 created "2016-06-24" @default.
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• W2045647632 date "2012-08-01" @default.
• W2045647632 modified "2023-10-05" @default.
• W2045647632 title "Uncovering interactions in Plackett–Burman screening designs applied to analytical systems. A Monte Carlo ant colony optimization approach" @default.
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• W2045647632 doi "https://doi.org/10.1016/j.talanta.2012.04.025" @default.
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