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Finding significant temporal and spatial patterns in industrial process data

Finding significant temporal and spatial patterns in industrial process data
寻找工业过程数据中重要的时间和空间模式
批准号:
412198-2011
负责人:
Sander, Jörg
金额:
$3.2万
依托单位:
依托单位国家:
加拿大
项目类别:
Collaborative Research and Development Grants
财政年份:
2012
资助国家:
加拿大
项目状态:
已结题
起止时间:
2012-01-01 至 2013-12-31

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中文摘要
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英文摘要
Industrial processes, such as those found at Syncrude, generate vast amounts of temporal and spatial. This data is typically generated by sensors used in monitoring the processes in order to maintain safe, reliable operation within the designed envelope of operation. For example, power levels applied to shovel ropes during operation change with both different operators and different locations, or a complex oil extraction process, monitored in terms of flow rates, density, composition, temperature, etc.
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Finding Groups in Big Data
  • 批准号:
    RGPIN-2016-04850
  • 项目类别:
    Discovery Grants Program - Individual
  • 资助金额:
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  • 财政年份:
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  • 依托单位:
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  • 批准号:
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  • 项目类别:
    Discovery Grants Program - Individual
  • 资助金额:
    $3.35万
  • 财政年份:
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  • 依托单位:
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  • 项目类别:
    Discovery Grants Program - Individual
  • 资助金额:
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