一种基于实证公式和图形穿越算法的快速方法,用于自动生成香味公式
Jiaxiao Cai1, Suxing Tuo1, Yanchun Li1
1Technology Center of China Tobacco Hunan Industrial Co., Ltd., Changsha, 410007, China.
Heliyon
|December 25, 2024
概括
本研究介绍了一种基于图形的新算法,用于自动化制造香水配方. 该方法通过分析成分关系和专家知识来提高设计效率和准确性,从而产生实际结果.
科学领域:
- 计算化学计算化学
- 化学信息学 化学信息学
- 香味科学 香味科学 香味科学
背景情况:
- 传统的香水设计在很大程度上依赖于香水师的专业知识和经验方法.
- 自动化香水配方创建需要复杂的数据分析和算法方法.
- 现有的方法在探索复杂的成分相互作用时可能缺乏效率和准确性.
研究的目的:
- 开发一种新的计算方法来优化香水设计.
- 为了提高自动香水配方生成的准确性和效率.
- 将经验数据与图形理论和制造香味的算法方法相结合.
主要方法:
- 使用图形理论构建了一个关系网络模型,以表示来自210个经验香味公式的成分组合.
- 开发了一个包含344种常见香料成分的综合数据库.
- 实施了深度先搜索算法,并结合了基于专家定义的约束条件的自动公式生成的统计策略.
主要成果:
- 成功创建了一个关系网络模型,说明了成分关系.
- 建立了一个能够生成新配方的自动香味配方创建算法.
- 验证了算法,成功创建了一个符合预期的花香,并证明了实际价值.
结论:
- 拟议的基于图形的方法显著提高了香水设计的效率和准确性.
- 实证数据,图形算法和专家知识的整合为自动化香水制造提供了一个强大的工具.
- 开发的算法在创建新型香水配方方面具有实际应用价值.
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