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A Methodology for Combining Symbolic Regression and Design of Experiments to Improve Empirical Model Building.

, , , и . GECCO, том 2724 из Lecture Notes in Computer Science, стр. 1975-1985. Springer, (2003)

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Другие публикации лиц с тем же именем

Symbolic regression in multicollinearity problems., и . GECCO, стр. 2207-2208. ACM, (2005)Competitive advantages of evolutionary computation for industrial applications., , , , , и . Congress on Evolutionary Computation, стр. 166-173. IEEE, (2005)Symbolic Regression In Design Of Experiments: A Case Study With Linearizing Transformations., , , и . GECCO, стр. 1043-1047. Morgan Kaufmann, (2002)Evaluating and ranking patents with multiple criteria: How many criteria are required to find the most promising patents?, , , , и . Comput. Chem. Eng., (2019)Pareto front genetic programming parameter selection based on design of experiments and industrial data., , , , и . GECCO, стр. 1613-1620. ACM, (2006)A Methodology for Combining Symbolic Regression and Design of Experiments to Improve Empirical Model Building., , , и . GECCO, том 2724 из Lecture Notes in Computer Science, стр. 1975-1985. Springer, (2003)Using evolutionary algorithms to suggest variable transformations in linear model lack-of-fit situations., , и . IEEE Congress on Evolutionary Computation, стр. 556-560. IEEE, (2004)Empirical Models with Self-Assessment Capabilities for On-Line Industrial Applications., , , , , и . IEEE Congress on Evolutionary Computation, стр. 3106-3113. IEEE, (2006)