Fractional-order calculus-based flower pollination algorithm with local search for global optimization and image segmentation

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Author(s)
Yousri, Dalia
Abd Elaziz, Mohamed
Mirjalili, Seyedali
Griffith University Author(s)
Year published
2020
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Introducing a novel approach to enhance the diversification and intensification propensities of the flower pollination algorithm (FPA) is the main aim of this paper. Therefore, the fractional-order (FO) calculus features are adopted to enhance the basic FPA local search ability and adaptive modify the harmonization coefficient among the FPA exploration and exploitation cores. The proposed Fractional-order FPA (FO-FPA) is examined in a number of experiments. Firstly, FO-FPA is tested with thirty-six benchmark functions with several dimensions. The proposed FO-FPA is compared with recent proved techniques based on several ...
View more >Introducing a novel approach to enhance the diversification and intensification propensities of the flower pollination algorithm (FPA) is the main aim of this paper. Therefore, the fractional-order (FO) calculus features are adopted to enhance the basic FPA local search ability and adaptive modify the harmonization coefficient among the FPA exploration and exploitation cores. The proposed Fractional-order FPA (FO-FPA) is examined in a number of experiments. Firstly, FO-FPA is tested with thirty-six benchmark functions with several dimensions. The proposed FO-FPA is compared with recent proved techniques based on several statistical measures and non parametric tests. Secondly, FO-FPA is implemented for a real application of the image segmentation and its results compared with state-of-the-art multi-level thresholding algorithms. The comparisons divulge the remarkable influence of merging FO with the basic FPA in improving the quality of the solutions and the acceleration of the convergence speed.
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View more >Introducing a novel approach to enhance the diversification and intensification propensities of the flower pollination algorithm (FPA) is the main aim of this paper. Therefore, the fractional-order (FO) calculus features are adopted to enhance the basic FPA local search ability and adaptive modify the harmonization coefficient among the FPA exploration and exploitation cores. The proposed Fractional-order FPA (FO-FPA) is examined in a number of experiments. Firstly, FO-FPA is tested with thirty-six benchmark functions with several dimensions. The proposed FO-FPA is compared with recent proved techniques based on several statistical measures and non parametric tests. Secondly, FO-FPA is implemented for a real application of the image segmentation and its results compared with state-of-the-art multi-level thresholding algorithms. The comparisons divulge the remarkable influence of merging FO with the basic FPA in improving the quality of the solutions and the acceleration of the convergence speed.
View less >
Journal Title
Knowledge-Based Systems
Volume
197
Copyright Statement
© 2020 Elsevier. Licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International Licence (http://creativecommons.org/licenses/by-nc-nd/4.0/) which permits unrestricted, non-commercial use, distribution and reproduction in any medium, providing that the work is properly cited.
Subject
Psychology
Science & Technology
Computer Science, Artificial Intelligence
Flower pollination algorithm