基于粒子群优化算法的新能源产业生态集成系统关键技术创新模式

IF 6.6 1区 计算机科学 Q1 Multidisciplinary
Shunjun Luo;Xiaoge Zhu;Jiasen Ran
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引用次数: 0

摘要

社会的发展离不开传统燃烧能源的使用。然而,人们对化石能源的过度开采导致化石能源逐渐短缺。寻找新能源(NE),发展新能源产业至关重要。自然生态系统具有稳定发展的特点。随着人工智能(AI)的发展,自然生态系统的结构被应用于新能源产业,形成了新能源产业生态集成系统。本文采用粒子群优化(PSO)算法对东北亚产业结构和资源进行优化,使东北亚产业具备可持续发展的能力。本文比较了传统东北亚产业和基于 PSO 算法的东北亚创新产业生态集成系统。实验结果表明,在东北地区车辆产业中,传统东北地区产业和基于 PSO 算法的东北地区创新产业生态系统的平均经济效益分别为 63.6% 和 77.2%。在东北电力行业,传统东北电力行业和基于 PSO 算法的东北电力创新行业生态系统的平均经济效益分别为 67.6% 和 80.4%。因此,在人工智能背景下,将 PSO 算法应用于东北亚产业生态集成系统可以提高东北亚产业的经济效益。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Key Technology Innovation Mode of New Energy Industry Ecological Integration System Based on Particle Swarm Optimization Algorithm
The development of society is inseparable from the use of traditional burning energy. However, people's excessive exploitation of fossil energy has led to the gradual shortage of fossil energy. It is essential to find New Energy (NE) and develop a new energy industry. The natural ecosystem has the characteristics of stable development. With the development of Artificial Intelligence (AI), the structure of the natural ecosystem has been applied to the NE industry, forming an NE industry ecological integration system. This paper uses Particle Swarm Optimization (PSO) algorithm to optimize the structure and resources of the NE industry, so that the NE industry has the capability of sustainable development. The traditional NE industry and the NE innovation industry ecological integration system based on PSO algorithm are compared. The experimental results show that in the NE vehicle industry, the average economic benefits of the traditional NE industry and the NE innovation industry ecosystem based on PSO algorithm are 63.6% and 77.2%, respectively. In the NE power generation industry, the average economic benefits of the traditional NE industry and the NE innovation industry ecosystem based on PSO algorithm are 67.6% and 80.4%, respectively. Therefore, in the context of AI, the application of PSO algorithm to the ecological integration system of NE industry could improve the economic benefits of NE industry.
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来源期刊
Tsinghua Science and Technology
Tsinghua Science and Technology COMPUTER SCIENCE, INFORMATION SYSTEMSCOMPU-COMPUTER SCIENCE, SOFTWARE ENGINEERING
CiteScore
10.20
自引率
10.60%
发文量
2340
期刊介绍: Tsinghua Science and Technology (Tsinghua Sci Technol) started publication in 1996. It is an international academic journal sponsored by Tsinghua University and is published bimonthly. This journal aims at presenting the up-to-date scientific achievements in computer science, electronic engineering, and other IT fields. Contributions all over the world are welcome.
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