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- W2955490980 abstract "The Flower Pollination Algorithm (FPA) is a modern heuristic technique that is applicable for the purposes of deriving best solution within several optimization tasks. This paper is a example of utilizing this metaheuristic procedure for the Probabilistic Neural Network (PNN) learning process. In this paper, for the purpose of classification, this type of Neural Network is applied to data sets drawn from the UCI Machine Learning Repository. Moreover, we concentrate upon investigating the inertial parameters of FPA, as well as the overfitting aspect." @default.
- W2955490980 created "2019-07-12" @default.
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- W2955490980 date "2019-05-03" @default.
- W2955490980 modified "2023-10-06" @default.
- W2955490980 title "Triggering Probabilistic Neural Networks with Flower Pollination Algorithm" @default.
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- W2955490980 doi "https://doi.org/10.1007/978-3-030-16024-1_14" @default.
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