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Titlebook: Computational Intelligence; 11th International J Juan Julián Merelo,Jonathan Garibaldi,Kurosh Madan Conference proceedings 2021 Springer Na

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樓主: broach
21#
發(fā)表于 2025-3-25 05:43:21 | 只看該作者
22#
發(fā)表于 2025-3-25 11:20:41 | 只看該作者
Noodle-Map Chaos: A Simple Exampleeness for high-dimensional samples: on the set of 653 predictors, we obtained 68% accuracy on average, whereas on the reduced set of 100 predictors, we could improve this result only up to 70%. Furthermore, this study introduces the most important predictor variables used in the generated Fuzzy Logi
23#
發(fā)表于 2025-3-25 12:48:28 | 只看該作者
J. L. Hudson,J. C. Mankin,O. E. R?ssleronomy ranking before and after compensating for route inclination and payload. We found that supplier depot and driver are the primary factors related to shrinkage, and that a relatively small fraction of depots and drivers cause the majority of shrinkage. Compensating for non-driver factors however
24#
發(fā)表于 2025-3-25 19:10:42 | 只看該作者
25#
發(fā)表于 2025-3-25 23:41:23 | 只看該作者
https://doi.org/10.1007/978-1-4612-1244-7roblem’s feature space is Boolean, without looking at the inner structure of the classifier. For such a classifier with a small feature space, a Boolean function describing it can be directly calculated, whilst for a classifier with a larger feature space, a sampling method is investigated to produc
26#
發(fā)表于 2025-3-26 01:13:42 | 只看該作者
27#
發(fā)表于 2025-3-26 04:25:28 | 只看該作者
An Empirical Study on Insertion and Deletion Mutation in Cartesian Genetic Programming problems are performed and the results show an improved search performance when these phenotypic mutations are used. The observed improvement of the search performance indicates that the insertion and deletion mutation techniques are beneficial for the use of CGP. The effectiveness of both mutation
28#
發(fā)表于 2025-3-26 12:12:53 | 只看該作者
29#
發(fā)表于 2025-3-26 14:02:07 | 只看該作者
30#
發(fā)表于 2025-3-26 19:38:50 | 只看該作者
Predicting Cardiovascular Death with Automatically Designed Fuzzy Logic Rule-Based Modelseness for high-dimensional samples: on the set of 653 predictors, we obtained 68% accuracy on average, whereas on the reduced set of 100 predictors, we could improve this result only up to 70%. Furthermore, this study introduces the most important predictor variables used in the generated Fuzzy Logi
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