Li Hao, Liao Bolin, Li Jianfeng, Li Shuai
College of Computer Science and Engineering, Jishou University, Jishou 416000, China.
School of Communication and Electronic Engineering, Jishou University, Jishou 416000, China.
Biomimetics (Basel). 2024 Jul 24;9(8):453. doi: 10.3390/biomimetics9080453.
The question "How does it work" has motivated many scientists. Through the study of natural phenomena and behaviors, many intelligence algorithms have been proposed to solve various optimization problems. This paper aims to offer an informative guide for researchers who are interested in tackling optimization problems with intelligence algorithms. First, a special neural network was comprehensively discussed, and it was called a zeroing neural network (ZNN). It is especially intended for solving time-varying optimization problems, including origin, basic principles, operation mechanism, model variants, and applications. This paper presents a new classification method based on the performance index of ZNNs. Then, two classic bio-inspired algorithms, a genetic algorithm and a particle swarm algorithm, are outlined as representatives, including their origin, design process, basic principles, and applications. Finally, to emphasize the applicability of intelligence algorithms, three practical domains are introduced, including gene feature extraction, intelligence communication, and the image process.
“它是如何工作的”这个问题激励了许多科学家。通过对自然现象和行为的研究,人们提出了许多智能算法来解决各种优化问题。本文旨在为有兴趣用智能算法解决优化问题的研究人员提供一份内容丰富的指南。首先,全面讨论了一种特殊的神经网络,它被称为归零神经网络(ZNN)。它特别用于解决时变优化问题,包括其起源、基本原理、运行机制、模型变体和应用。本文提出了一种基于归零神经网络性能指标的新分类方法。然后,概述了两种经典的受生物启发的算法——遗传算法和粒子群算法作为代表,包括它们的起源、设计过程、基本原理和应用。最后,为强调智能算法的适用性,介绍了三个实际领域,包括基因特征提取、智能通信和图像处理。