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Optimizing Materials Discovery with Quantum and Classical Machine Learning Techniques
技术
- 分析与建模 - 机器学习
适用行业
- 消费品
- 运输
用例
- 预测性维护
- 公共交通管理
服务
- 数据科学服务
- 培训
挑战
作为全球最大的化学品生产商，巴斯夫不断为消费品、交通、医疗保健、农业、能源等领域开发新材料。他们正在探索如何在当今的经典计算机上利用人工智能和量子技术来增强现有的化学信息学解决方案，特别是可以预测新材料分子特性的机器学习模型。
关于客户
巴斯夫是全球最大的化学品生产商，涉足消费品、交通、医疗保健、农业和能源等多个行业的新材料开发。他们专注于可持续和创新的解决方案。
解决方案
巴斯夫正在与 Zapata 合作，使用 Orquestra 平台将其专有的量子增强机器学习技术与最先进的经典方法进行基准测试。他们正在探索用于预测分子特性的机器学习方法，将特征选择和分类作为监督学习算法的子例程。此外，巴斯夫还利用 Zapata 的 GEO 技术来优化整个价值链的运营，从原材料采购到生产设施选址。
相关案例.
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Case Study
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