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Nationwide Statistical Data on Electric Power Industry in Year 2000(Predicted Value)
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《Electricity》 2001年第1期54-54,共1页
关键词 Nationwide Statistical data on electric power Industry in Year 2000
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Data on Electric Power Production of the State Power Corporation in Year 2000(Predicted Value)
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《Electricity》 2001年第1期55-55,共1页
关键词 data on electric power Production of the State power Corporation in Year 2000
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Data on Electric Power Production of the State Power Corporation in Year 2001
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《Electricity》 2002年第1期55-55,共1页
关键词 data on electric power Production of the State power Corporation in Year 2001
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Knowledge Model for Electric Power Big Data Based on Ontology and Semantic Web 被引量:19
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作者 Yanhao Huang Xiaoxin Zhou 《CSEE Journal of Power and Energy Systems》 SCIE 2015年第1期19-27,共9页
It is very important for the development of electric power big data technology to use the electric power knowledge.A new electric power knowledge theory model is proposed here to solve the problem of normalized modele... It is very important for the development of electric power big data technology to use the electric power knowledge.A new electric power knowledge theory model is proposed here to solve the problem of normalized modeled electric power knowledge for the management and analysis of electric power big data.Current modeling techniques of electric power knowledge are viewed as inadequate because of the complexity and variety of the relationships among electric power system data.Ontology theory and semantic web technologies used in electric power systems and in many other industry domains provide a new kind of knowledge modeling method.Based on this,this paper proposes the structure,elements,basic calculations and multidimensional reasoning method of the new knowledge model.A modeling example of the regulations defined in electric power system operation standard is demonstrated.Different forms of the model and related technologies are also introduced,including electric power system standard modeling,multi-type data management,unstructured data searching,knowledge display and data analysis based on semantic expansion and reduction.Research shows that the new model developed here is powerful and can adapt to various knowledge expression requirements of electric power big data.With the development of electric power big data technology,it is expected that the knowledge model will be improved and will be used in more applications. 展开更多
关键词 electric power big data knowledge model ONTOLOGY semantic web
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