A novel multi-level image segmentation algorithm via random opposition learning-based Aquila optimizer

IF 0.9 4区 计算机科学 Q4 COMPUTER SCIENCE, SOFTWARE ENGINEERING International Journal of Wavelets Multiresolution and Information Processing Pub Date : 2023-04-20 DOI:10.1142/s0219691323500182
Jia Cai, Tianhua Luo, Zhilong Xiong, Yi Tang
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引用次数: 0

Abstract

Aquila optimizer (AO) is an efficient meta-heuristic optimization method, which mimics the hunting style of Aquila in nature. However, the AO algorithm may suffer from immature convergence during the exploitation stage. In this paper, two strategies are elegantly employed into conventional AO, such as random opposition-based learning and nonlinear flexible jumping factor, which can efficiently enhance the performance of conventional AO. Experiments on [Formula: see text] benchmark functions and image segmentation demonstrate the effectiveness of the proposed algorithm. Comparison with several state-of-the-art meta-heuristic optimization techniques indicates the efficacy of the developed method.
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一种新的基于随机对立学习的Aquila优化器多级图像分割算法
Aquila优化器(AO)是一种高效的元启发式优化方法,它模仿了自然界中Aquila的狩猎方式。然而,AO算法在开发阶段可能存在不成熟的收敛性。本文将基于随机对立学习和非线性柔性跳跃因子两种策略巧妙地应用于传统AO中,有效地提高了传统AO的性能。通过[公式:见文本]基准函数和图像分割实验验证了算法的有效性。与几种最先进的元启发式优化技术的比较表明了所开发方法的有效性。
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来源期刊
CiteScore
2.60
自引率
7.10%
发文量
52
审稿时长
2.7 months
期刊介绍: International Journal of Wavelets, Multiresolution and Information Processing (hereafter referred to as IJWMIP) is a bi-monthly publication for theoretical and applied papers on the current state-of-the-art results of wavelet analysis, multiresolution and information processing. Papers related to the IJWMIP theme are especially solicited, including theories, methodologies, algorithms and emerging applications. Topics of interest of the IJWMIP include, but are not limited to: 1. Wavelets: Wavelets and operator theory Frame and applications Time-frequency analysis and applications Sparse representation and approximation Sampling theory and compressive sensing Wavelet based algorithms and applications 2. Multiresolution: Multiresolution analysis Multiscale approximation Multiresolution image processing and signal processing Multiresolution representations Deep learning and neural networks Machine learning theory, algorithms and applications High dimensional data analysis 3. Information Processing: Data sciences Big data and applications Information theory Information systems and technology Information security Information learning and processing Artificial intelligence and pattern recognition Image/signal processing.
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