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Performance evaluation and optimization of distributed collaborative operation and maintenance control platform based on information processing.

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Τίτλος: Performance evaluation and optimization of distributed collaborative operation and maintenance control platform based on information processing.
Συγγραφείς: Ma, Jianwei, Fu, Tongfu, Wang, Wenhua, Zhou, Zhongqiang, Liang, Ling
Πηγή: Intelligent Decision Technologies; Mar2025, Vol. 19 Issue 2, p1240-1252, 13p
Θεματικοί όροι: Multisensor data fusion, Information processing, Resource allocation, Electronic data processing, Acquisition of data
Περίληψη: Aiming at the problems of data isolation, poor real-time performance, low efficiency, and lack of intelligent cooperation in traditional operation and maintenance, this paper proposes a distributed cooperative operation and maintenance control platform based on information processing. Through the steps of data distributed collection, pre-processing, fusion analysis, and dynamic resource allocation, the data processing efficiency, system response speed, resource utilization, and decision accuracy are significantly improved. The experimental results show that compared with the traditional method, the platform improves the data processing efficiency to 500GB/hour, the system response time to 2 s, the resource utilization rate to 68.75%, and the decision accuracy to 90%, which significantly enhances the intelligence and real-time of operation and maintenance control. [ABSTRACT FROM AUTHOR]
Copyright of Intelligent Decision Technologies is the property of Sage Publications Inc. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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  Data: Performance evaluation and optimization of distributed collaborative operation and maintenance control platform based on information processing.
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  Data: <searchLink fieldCode="AR" term="%22Ma%2C+Jianwei%22">Ma, Jianwei</searchLink><br /><searchLink fieldCode="AR" term="%22Fu%2C+Tongfu%22">Fu, Tongfu</searchLink><br /><searchLink fieldCode="AR" term="%22Wang%2C+Wenhua%22">Wang, Wenhua</searchLink><br /><searchLink fieldCode="AR" term="%22Zhou%2C+Zhongqiang%22">Zhou, Zhongqiang</searchLink><br /><searchLink fieldCode="AR" term="%22Liang%2C+Ling%22">Liang, Ling</searchLink>
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  Data: Intelligent Decision Technologies; Mar2025, Vol. 19 Issue 2, p1240-1252, 13p
– Name: Subject
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  Data: <searchLink fieldCode="DE" term="%22Multisensor+data+fusion%22">Multisensor data fusion</searchLink><br /><searchLink fieldCode="DE" term="%22Information+processing%22">Information processing</searchLink><br /><searchLink fieldCode="DE" term="%22Resource+allocation%22">Resource allocation</searchLink><br /><searchLink fieldCode="DE" term="%22Electronic+data+processing%22">Electronic data processing</searchLink><br /><searchLink fieldCode="DE" term="%22Acquisition+of+data%22">Acquisition of data</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: Aiming at the problems of data isolation, poor real-time performance, low efficiency, and lack of intelligent cooperation in traditional operation and maintenance, this paper proposes a distributed cooperative operation and maintenance control platform based on information processing. Through the steps of data distributed collection, pre-processing, fusion analysis, and dynamic resource allocation, the data processing efficiency, system response speed, resource utilization, and decision accuracy are significantly improved. The experimental results show that compared with the traditional method, the platform improves the data processing efficiency to 500GB/hour, the system response time to 2 s, the resource utilization rate to 68.75%, and the decision accuracy to 90%, which significantly enhances the intelligence and real-time of operation and maintenance control. [ABSTRACT FROM AUTHOR]
– Name: Abstract
  Label:
  Group: Ab
  Data: <i>Copyright of Intelligent Decision Technologies is the property of Sage Publications Inc. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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        Value: 10.1177/18724981241291435
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        Text: English
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      – SubjectFull: Resource allocation
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              Text: Mar2025
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