基于群体智能的蚕丝纳米纤维材料质量评价
Material quality assessment of silk nanofibers based on swarm intelligence
摘要：
本文提出了一种基于人工爬虫模型的纹理分析方法。我们的方法假设每个代理可以与环境和彼此交互。演化过程根据规则集收敛到平衡状态。对于每个纹理图像，特征向量由每个时间的活代理曲线的签名组成。实验结果表明，将最小签名和最大签名合并为一个可以提高分类率。此外，我们率先使用自主智能体表征丝素蛋白支架。结果表明，我们的方法可以成功地用于纹理分析。
英文摘要：
In this paper, we propose a novel approach for texture analysis based on artificial crawler model. Our method assumes that each agent can interact with the environment and each other. The evolution process converges to an equilibrium state according to the set of rules. For each textured image, the feature vector is composed by signatures of the live agents curve at each time. Experimental results revealed that combining the minimum and maximum signatures into one increase the classification rate. In addition, we pioneer the use of autonomous agents for characterizing silk fibroin scaffolds. The results strongly suggest that our approach can be successfully employed for texture analysis.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
