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AES 通过 AI 和 H2O.ai 实现能源业务转型
AES 是一家领先的可再生能源公司，面临着加速大规模向可再生能源转型的挑战。这种业务转型需要数字和人工智能转型，以更好地预测和优化可再生能源的能源输出、预测故障并优化负载分配。该公司必须处理风力涡轮机预测性维护、水力发电厂能源招标策略和智能电表的复杂性。风力涡轮机有许多运动部件，需要承受恶劣的环境，其维护成本特别高且耗时。该公司还需要优化其能源招标策略，以最大限度地提高水力发电厂的收入。此外，该公司必须管理超过一百万台智能电表，这些电表有时会出现维护问题或被滥用。
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H2O.ai empowers New South Wales Government To Deliver Exceptional Services for its Citizens with AI
The New South Wales (NSW) Government wanted to build out its data practice and initiatives. They needed to enable its analysts to draw upon data science and automatic machine learning platforms to help find answers, pinpoint solutions and use data to create better services for all. The government was looking for a solution that could improve the accuracy of its predictive models and empower its team of data scientists to build models faster.
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H2O for Real Time Fraud Detection
Organizations responsible for fraud prevention are facing a host of challenges at the transaction, account, and network-level to detect fraudulent behavior and suspicious activities. Fraudulent transactions are rare, but costly if they aren’t detected. In the credit card business, for example, third-party fraud accounts for roughly 4 out of every 10,000 transactions. Modeling rare events is difficult, like finding a needle in a haystack. For best results, gather as much data as possible, and use the most advanced techniques available.
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