Energy big data acquisition and application based on service portfolio quality

Sun, Ping; Gu, Lingang

doi:10.1016/j.seta.2021.101134

Cited by 4 publications

(2 citation statements)

References 27 publications

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“…Retaining the amount of information in the security assessment requirements dimension, on the basis of which it corresponds to a valid assessment factor [6][7][8]. First, in the information flow of any security assessment requirement in the energy transaction data space, let a be an individual numerator of a node in that information flow, then the transformation relationship c between an energy transaction data information node and its corresponding assessment numerator is calculated as equation ( 3):…”

Section: Building a Model For Assessing The Security Of Energy Tradin...mentioning

confidence: 99%

A Method for Assessing the Security of Energy Trading Data Based on Big Data and the Pagerank Algorithm

Ding¹,

Zhang²,

Yang³

et al. 2023

Proceedings of the 2nd International Conference on Bigdata Blockchain and Economy Management, ICBBEM 2023, May 19–21, 2023, Han

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The current assessment of the security of energy transaction data has vague evaluation dimensions, resulting in large errors in the assessment results. To this end, we propose a method for assessing the security of energy transaction data based on big data and the Pagerank algorithm. Determine assessment requirements based on big data and obtain assessment requirements based on six dimensions. Construct a security assessment model and calculate the indicator weights for this model. The assessment results are obtained dynamically based on the Pagerank algorithm. Experiments show that the evaluation results of the method have a small error, with an average error of only 0.22%, which has a high application value.

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Section: Building a Model For Assessing The Security Of Energy Tradin...mentioning

confidence: 99%

A Method for Assessing the Security of Energy Trading Data Based on Big Data and the Pagerank Algorithm

Ding¹,

Zhang²,

Yang³

et al. 2023

Proceedings of the 2nd International Conference on Bigdata Blockchain and Economy Management, ICBBEM 2023, May 19–21, 2023, Han

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show abstract

“…Shah et al [24] constructed a QoS-based automation solution using end-to-end multi-agents to provide service requesters with the most suitable web services. Sun [25] proposed a method of decomposing the quality of QoS indicators in the Internet of Things environment, which can improve the QoS calculation speed of the service composition. The use of QoS in optimizing geospatial service composition is based on the evaluation of service quality and dynamically composite services according to QoS.…”

Section: Qos In Geospatial Servicementioning

confidence: 99%

An Augmented Geospatial Service Web Based on QoS Constraints and Geospatial Service Semantic Relationships

Jin

Liang

et al. 2022

IJGI

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The service network is capable of addressing large-scale service composition. However, existing service network works still have several limitations. Prior knowledge, such as expert-defined service chains, is not incorporated into the service network. QoS constraints are less considered in the service network, and thus the generated service chain does not always satisfy the optimal QoS constraints. Additionally, some basic services also require outputs to be used directly as inputs, which the service network cannot provide. To address these limitations, this paper proposes a geospatial service web (GSW) model named SR-QoS-GSW that incorporates service semantic relationships and QoS information. The SR-QoS-GSW model consists of atomic services and composite services that consider QoS, processing services, data services, and relationships among them. A SR-QoS-GSW prototype was developed using 570 atomic services and 27 composite services and evaluated using two case studies—a river network extraction and an urban housing selection. Then, the information entropy and time complexity between SR-QoS-GSW and the existing service network were compared. The results show that geospatial service chains can be created more efficiently by incorporating existing service chains as composite services. Integrating QoS information into the GSW would allow service composition algorithms to generate service chains that satisfy optimal QoS constraints. The outputs of services used as new inputs with additional self-matching relationships also give the service network greater flexibility. Finally, the analysis of the information entropy and time complexity verified the increased diversity and decreased the search space of the SR-QoS-GSW.

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Coupling big data and life cycle assessment: A review, recommendations, and prospects

Tian

Xie

2023

Ecological Indicators

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Energy big data acquisition and application based on service portfolio quality

Cited by 4 publications

References 27 publications

A Method for Assessing the Security of Energy Trading Data Based on Big Data and the Pagerank Algorithm

A Method for Assessing the Security of Energy Trading Data Based on Big Data and the Pagerank Algorithm

An Augmented Geospatial Service Web Based on QoS Constraints and Geospatial Service Semantic Relationships

Coupling big data and life cycle assessment: A review, recommendations, and prospects

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