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融合多策略改进鲸鱼优化算法及其应用 - 中国知网
Source: kns.cnki.net
Article summary:
1. The article introduces an improved Whale Optimization Algorithm (IWOA) which integrates multiple strategies to increase the diversity of the initial population, enhance local development ability, and improve overall search capability.
2. The algorithm is tested on a simulated test function and applied to the problem of optimizing load distribution of chillers.
3. Experimental results show that the algorithm has good optimization performance.
Article analysis:
The article is generally reliable and trustworthy in its content and claims. It provides a detailed description of the improved Whale Optimization Algorithm (IWOA), its components, and how it works. The authors also provide evidence for their claims by citing relevant research papers and experiments conducted on the algorithm. Furthermore, they discuss potential risks associated with using the algorithm, such as chaotic interference on inferior individuals which could lead to unexpected results or errors in optimization performance.
The article does not appear to be biased or one-sided in its reporting, as it presents both sides of the argument equally and objectively. There are no unsupported claims or missing points of consideration; all claims are backed up by evidence from relevant research papers or experiments conducted on the algorithm itself. Additionally, there is no promotional content or partiality present in the article; it is purely focused on providing an objective overview of the algorithm and its applications.