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- W2103298757 abstract "Polynomial Symbolic Regression tree-based Genetic Programming faces considerable obstacles towards the discovery of a global optimum solution; three of these being bloat, premature convergence and a compromised ability to retain building block information. We present a building block conservation and extension strategy that targets these specific obstacles. Experiments conducted demonstrate a superior performance of our strategy relative to the canonical GP. Further our strategy achieves a competitive reduction in bloat." @default.
- W2103298757 created "2016-06-24" @default.
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- W2103298757 date "2012-11-01" @default.
- W2103298757 modified "2023-09-25" @default.
- W2103298757 title "A building block conservation and extension mechanism for improved performance in Polynomial Symbolic Regression tree-based Genetic Programming" @default.
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- W2103298757 doi "https://doi.org/10.1109/nabic.2012.6402250" @default.
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